THE LIFE OF A BAYESIAN BOY TOM LEONARD'S LIFE STORY

 

THE LIFE OF A BAYESIAN BOY   Tom Leonard   Retired Professor of Statistics, Universities of Wisconsin and Edinburgh   Edinburgh, Scotland, May 2012   Tom Leonard (left) aged 4 with his brother and cousins   This is a largely humorous account of Tom Leonard’s early life, and his academic career in Statistics at the Universities of London (1966-72), Warwick (1972-80), Wisconsin (1979-1996) and Edinburgh (1995-2001) that was influential in numerous application areas of his Bayesian-Fisherian approach to mathematical statistics. These include medicine, econometrics, psychometrics, educational testing, finance, business, geophysics, animal breeding, substance abuse, forensic science, and the law.          Tom, for example, re-addresses the Lindley-Smith controversy and its effects on his career, together with George Box’s incisive impact on applied statistical methodology, and the military activities that led to the demise of the Math Research Center at the University of Wisconsin-Madison.          The history surrounding Tom’s pivotal December 1989 speech in Madison, Wisconsin on gay discrimination in the military is documented and appended.  Koutsky’s Hypothesis, which addresses the genesis of gay and lesbian people, is described in Chapter 6.          Further drama rears its head on unexpected occasions during the narrative. We should always feel a touch of concern about potential ripples from above. Tom Leonard - The Life of a Bayesian Boy   CHAPTER 1: EARLY LIFE   The River Yealm at Newton Ferrers   My life began when I was conceived in the Church House in Beverley, Yorkshire, where Oliver Cromwell reportedly dined with the Royalist mayor before hiding the  Roundhead silver in the attic. My father coated the mahogany woodwork with white paint, but Cromwell’s treasure was discovered by another tenant years later. I am descended from the Barons Hoskyns, via an errant son of Rev. Dr. Francis Bryant of Peter Tavy and Jane Hoskyns-Abrahall, and my full name is Thomas Hoskyns Leonard.   My father, Captain Cecil Leonard (1913 - 2001)                       I was born in Flete House, Yealmpton, Devonshire in 1948 (I have only recently learnt that Flete House is not a castle, despite its spectacular appearance. My apologies to my colleagues in Wisconsin!), and grew up in Plymouth between 1952 and 1966 after a spell in a large apparently-haunted house on the Beverley Road that backed into a slum.           I lived in a mid-terrace house in Mannamead, played chess and rugby at Sutton High, where I was a prefect, attended Plymouth Argyle’s home games with my father (I remember watching Jimmy Greaves score for Spurs in a devastating five-goals-to-one cup tie in 1962), and went caving and diving with my older brother; I was a qualified snorkel diver with the British Sub-Aqua Club and enjoyed exploring the seabed off the South Devon and Cornish coasts.           As a Second World War army officer, my father Cap’n Cecil Leonard always impressed me with his war stories (North Africa, Sicily, Italy, Palestine, the Rhine and on to meet the Russians surrounding Berlin!); he was the south-western branch manager for Amalgamated Dental, and during the 1980s and 1990s he Tom, 1986 was to spend many happy months of his retirement with me in my house by Lake Wingra in Madison, where he befriended George Box.   [As well as preserving old recordings of the Goons, George was a fan of Captain Pirate Prentice in Thomas Pynchon’s Gravity’s Rainbow; I sometimes suspected him of inventing the character himself, together with Teddy Bloat; I even wondered whether George was the mysterious Pynchon himself, but the real author seems to have finally surfaced!]   In Sutton High School 2nd XV Rugby Team (1965-66). Tom is 5th from the left on the top row.   In 1966, I took the Great Western train from Plymouth to Paddington to study Mathematics at Imperial College London.  When we reached the spectacular coastline between Teignmouth and Dawlish (where Adrian Smith was born), the waves crashed against our carriage window and I felt quite spooked.          While I’d found maths to be quite boring (while getting bullied ; I’m still totally neurotic!) at my remarkably Dickensian backstreet grammar school, I was useless at Physics and Chemistry practicals, and couldn’t even cope with a pipette. Therefore maths was the only subject that I could hope to competently study at University.          I went to Imperial College, instead of Exeter, because my older brother was studying Chemical Engineering there, and because I fluked an A grade in A-level Pure Maths rather than the anticipated C. My ambitions were rather limited, to say the least. I’d actually wanted to go into banking instead, but my mother was very determined.   Flete House, Devon   Mothecombe Beach   by Thomas Hoskyns Leonard   They will scatter my ashes To the tune of heavenly bands On the majestic golden sands Which the waters of the Erme reach On Mothecombe Beach. There I ran with my black swimming ring As a precocious child of medium size And built mansions and castles For the waves to vaporize, Close to the rocks on the Flete Estate Where the son of Lord Mildmay met his fate. There I sat on the sands as the tides rippled in, Savouring the blend and just about everything. When I was festering in lands far away, I thought of the river of my birth That has nurtured me to this day. I remembered pretty Yvette, Great Auntie May, And the picnics and ball games Which kept me in sway, And once again became happy and gay. Now, while the Grim Reaper waits My mind returns there at will And I only hope to be permitted One more walk Down God’s sacred hill.   The Erme Estaury at Mothecombe   Tom Leonard - The Life of a Bayesian Boy       CHAPTER 2: IMPERIAL COLLEGE LONDON               J.H. Morrison   D.P.Y. Palmer   R. Griffith-Jones   T. Leonard   C.J. Ing   D. Shield   During my first year in South Kensington, I found the Pure and Applied Maths courses extremely difficult to assimilate, and I don’t think that this was entirely my fault. For example, we were taught convergence and continuity by a bird-like lecturer who muttered to the blackboard in a huge hall in the Huxley Building.          Professor David Cox’s course in Statistics was however quite inspiring. By the time I graduated, he and his colleagues were to give me a solid grounding in classical Fisherian/ Frequentist statistics that provided a basis for my entire career. Indeed, I still regard myself as a Fisherian at heart, despite the influences of the Bayesianism that was forced upon me in 1970 when I needed an S.R.C. grant to study for my Ph.D. My second year was a disaster , and my personal tutor advised me to go into school teaching. After over-focussing on chess, beer and women, and taking time out to track Manchester United’s remarkable success in the European Cup (Best, Law and Charlton!), I flunked out with an average mark of 25% and a zero in Statistics. I was fortunately able to repeat and, with the encouragement of my very determined wife (a student in Russian at the School of Slavonic Studies on Russell Square and later a lecturer in economics at the University of Wolverhampton), I achieved two alphas, a beta and a gamma in the Summer of 1969. [One of my daughters was to achieve a Masters in Economics at the University of Warwick, with a specialism in Econometrics, while another graduated in medicine from Leeds.] During my final year, Dr. Anne Mitchell took me under her wing, and I greatly benefited from her unflagging support while focussing on courses in Statistics and O.R., measure theory from the indomitable Mrs. Dowker (who’d studied at the feet of Kolmogorov) and mathematical probability from Ron Doney. I learnt about applied statistics from an affable visiting Australian from Flinders called Jim Douglas, and Experimental Design from Agnes Herzberg, though I didn’t understand confounding. [See item 7 of CDC section for descriptions of my undergraduate vacation work with Clerical and Medical (1969) and the Metal Box Company(1970)]   Tom (right) aged 21 with his brother (aged 22) and his sister-in-law pictured at Tom's wedding in March 1969     Tom Leonard - The Life of a Bayesian Boy       CHAPTER 3: UNIVERSITY COLLEGE LONDON   Sir Adrian Smith, FRS Dennis V. Lindley Philip Dawid Tony O'Hagan Mervyn Stone     After I’d confounded myself with a first, Anne Mitchell contacted the University of Glasgow, where I would have studied with David Silvey (what a chance missed!) but after I’d prevaricated about moving to Scotland, she sent me to University College London, on Gower Street, where I was accepted to study for an intensively difficult advanced level Masters and a Ph.D. in the first ever university Statistics department, created by Karl Pearson in 1911.          My postgraduate supervisor Dennis V. Lindley was regarded as a world leader in Bayesian Statistics, having been converted to the faith by (the highly axiomatic and extremely eccentric) Jimmie Savage (whose religiously normative approach to expected utility had already been refuted by Maurice Allais) during a sabbatical to Chicago in 1954.          Dennis held the premier statistics chair in Britain; when he moved from Aberystwyth in 1967, an observer said that it was as though a Jehovah’s Witness had been elected Pope. He’d succeeded Karl Pearson’s son Egon, after some detailed negotiations with the UCL chancellor, and the indomitable Florence David felt persuaded to make her move to Riverside permanent. [While poor Florence didn’t even take to the normal distribution, she’d taught traditional applied statistics to a whole generation of UCL students, including Tony O’Hagan, and was well regarded. She seems to havc been seriously maligned by the Berkeley-school Californians, even though she was highly regarded at Riverside, and  there may have been a touch of homophobia in this. She later wrote to George Box, after one of his students had applied to her for an assistant professorship, saying that, ‘I had to explain to your student that we don’t have Bayesians at Riverside.’]          Dennis, a former Cambridge don, took a dim view of over-officious university administrators and followed Sir Ronald Fisher, another predecessor at University College, in this highly laudable respect. However, Fisher was totally eccentric, and once battered one of the ‘beefeaters’ guarding the quadrangle at UCL for being impolite to a woman companion who was trying to climb through a window. Dennis came across to me as a kindly, though superficially arrogant, man with a velvet glove but no iron fist. He encouraged me to try to solve my Ph.D. problem while studying for my Masters.          Within a few weeks I was able to extend Dennis’s method for the estimation of several exchangeable means and variances (that he’d extended to M-group regression in Iowa City during a remunerative consultancy for the American College Testing program with Mel Novick) to simultaneous inference and shrinkage estimation for several binomial probabilities. I did this by employing logistic transformations and non-conjugate hierarchical prior distributions, and these devices lead to my very first paper in an international journal (Bayesian Methods for Binomial Data, Biometrika 1972).     Jack Good            My friend Irving Jack Good (with whom I corresponded  about Alan Turing and their multinomial shrinkage estimators for cryptanalysis at Bletchley Park, which were instrumental in solving the Nazi codes) did not believe that my more general Logit/ First Stage Multivariate Normal Prior / hierarchical approach to the analysis of categorical data was sufficiently recognised by other Bayesians. Nevertheless, Alan Agresti and several other authors seem to think that it was a pioneering contribution, along with my external examiner’s (Patricia Altham’s) novel analysis of measures of association for 2x2 contingency tables. Indeed, many others have followed in my footsteps. [See items (4) and (5) of CDC section for discussions of Jim Albert’s later contributions, and of my 1978 Imperial College short-course lecture notes] In my Biometrika 1972 paper, I used my method to calculate shrinkage estimates for the pass rates at several different colleges. Philip. J. Smith of the Pacific Halibut Commission applied my approach to estimate the proportions of halibut in several different catches, and implemented various generalisations of my methodology. [My logit/normal first-stage-prior approach to the analysis of categorical data was reviewed by Leonard and Hsu (1994) in Aspects of Uncertainty: A Tribute to D.V. Lindley (edited by Peter Freeman and Adrian Smith). We also reported an Empirical Bayes analysis I’d developed in about 1977 and relating to the simultaneous estimation of the parameters of several multinomial distributions, via a multivariate normal prior for the different sets of logits.         When we applied the methodology to O-level data for 40 London high schools, we discovered that the posterior estimates of the grade rates smoothed the raw proportions in a highly complex fashion.          Leonard and Novick (Journal of Educational Statistics, 1986) describe a further educational testing study in relation to another contingency table, that summarizes their Marine Corps data. Leonard and Hsu (Annals of Statistics, 1992) report an analysis of a portion of the Project Talent American High School Data, where the observations are raw scores.] I shared my office at University College with Adrian F.M. Smith, a wonderfully inspirational and charismatic Adonis of a man who was to move on to a highly accomplished career[Don at Keble College Oxford, translator of the prestigious works of Bruno De Finetti, many successful Ph.D. students including Michael Goldstein and David Spiegelhalter,  Principal of Queen Mary College London, F.R.S., and a couple of top national leadership positions. Knighted in 2010], and with Daruish Haghighi-Talab, a Persian gentleman with an immense black beard, who studied road systems and was to become a Deputy Director of Official Statistics in Iran. The skylight in our office was often left open. This was to become a bone of contention in 1977 after Peter Freeman had moved in, and when an over-diligent university administrator insisted that the skylight should be kept closed. During the kafuffle that ensued, Dennis Lindley retired at age 54, albeit with a generously increased pension. He toured the world with his wife Joan into his sixties and a generation of postgraduates missed out on his inspirational guidance. Six other students studied for the Masters degree at University College at the same time as me, including my Glaswegian friends Ben Torsney and Jim McNicol, and a very nice man from Malaysia. We all took a core measure-theoretic course on Bayesian Inference from Phil Dawid, a brilliant junior lecturer, also out of Imperial College, who was just a year older than me and more recently became a professor at Cambridge.          I was particularly impressed by Phil’s description of Alan Birnbaum’s Likelihood Principle, its easy justification via the Sufficiency and Conditionality Principles, and the way it sorted the sheep and the goats in statistical methodology. Despite objections by George Barnard and others, I still find the proof of Birnbaum’s 1962 theorem to be extremely convincing and not at all tautologous. [The Neyman-Fisher factorization theorem is the key to the whole issue. It is this theorem that introduces the key concept of likelihood into statistical inference, based upon purely frequency considerations, and Birnbaum applies it to an ingeniously constructed mixed experiment to extend its influence to two simple experiments that investigate the same unknown parameter. Birnbaum has been described as one of the most profound thinkers in Statistics ever, and he was a buddy of Adrian Smith. He was however highly introspective, and took his own life in London in 1976. I have always empathised with him, particularly because of the way he was mistreated by other leading psychometricians during the 1960s. He was seriously anti-authoritarian and there are some parallels between our life stories] Phil fully generalised Ericson’s method for Linear Bayes estimation, and our homework was therefore light years ahead of the literature. (He later expressed his irritation at the alternative  procedure I used to quickly derive the estimates during the final exam, though that was in a special case.).          Phil’s parameterization, using degrees of freedom and prior sample sizes, of the conjugate analysis for the linear model with unknown variance was also superbly simple. This parameterization does not appear to have been published until 1986 when J.J. Shiau (one of Grace Wahba’s Ph.D. students) successfully applied it to partial spline models after I’d included it on my Statistics 775 course in Madison.            The entire theory of linear splines can of course be regarded as a special case of the very straightforward Gaussian prior Bayesian paradigm, and I’ve never quite understood what all the fuss was about and why we need to explicitly refer to them at all, though it is important not to over-parameterize when sensibly modelling the prior mean value function and covariance kernel. [an exponential quadratic prior kernel often works better than an autoregressive kernel since the posterior mean value function can then be infinitely differentiable. See Hsu and Leonard, Biometrika, 1997 where we used a semi-parametric multiple regression and residual analysis to investigate a binary data set that correlated the mortality of mice with time of exposure to NO2 and degree of exposure. It confirmed John’s tenure at UCSB. Some of the statistical ideas originated from one of my 1982 MRC technical reports, which described my Bayesian approach to semi-parametric logistic regression. See also Raynor, O’Sullivan and Yandell (JASA, 1985)]. I thought that the correspondence between Bayes estimates and smoothing splines was established as early as 1970 by Kimeldorf and Wahba, in a paper in Ann. Math. Statist. that was cited by 468 other authors. One of Grace’s students was much later quite irritating in the way he mimicked my Bayesian density smoothing techniques with non-linear smoothing splines, though he later referenced me quite generously.          Many published spline techniques employ a cross-validation technique to empirically estimate a smoothing parameter called lambda. However such techniques usually either mimic or recursively modify Mervyn Stone’s pioneering cross-validation method published in JRSSB (1974, with Discussion) and JRSSB (1977). All the 1970-71 Masters students at University College were expected to learn advanced probability theory, including convolution semi-groups and domains of attraction, from Feller Volume 2, but Dieter Girmes would come in for weeks on end, wave the book at us, and tell us about his latest statistical consultancy. We therefore had to assimilate Feller largely on our own.          Dennis Lindley taught me educational testing in the Princeton tradition, Markov decision processes (with stationarity theorems that were later republished out of a Department of Decision Theory in Manchester!) from the book by Sheldon Ross, and Masanao Aoki’s stochastic control theory in all its glory. Mervyn Stone taught an option on Art Dempster-style multivariate analysis, with ellipsoids looking like spaceships and which made me feel like a space cadet. While we didn’t learn any real statistics or Berkeley-style asymptotics, this was a Masters degree to be reckoned with. (Derek Teather and I were awarded distinctions. I only say this to emphasise that I was extremely able at that stage in my life) [During a trip to visit the Rev. Thomas Bayes’ grave in Bunhill Cemetery, Moorgate, the caretaker advised Mervyn Stone that Bayes was responsible for getting rockets to the moon. This was doubtlessly because of Aoki’s applications of Bayes theorem to stochastic control theory.]   Thomas Bayes' family grave   After I’d solved my Ph.D. research problem, as initially stated, Dennis gave me a much more difficult, and long unsolved, problem, the Bayesian smoothing of histograms. He’d wanted to use an autoregressive prior for several years, but couldn’t decide on which parameterization to use.          I’m still not quite sure how delighted  Denis really was when I solved the technical problem (including a tricky approximate prior to posterior analysis) that very afternoon, while recovering from several lunchtime beers with my fellow students, by assuming an autoregressive prior process for a set of sequentially chosen multinomial log contrasts. The published version in Biometrika 1973 refers instead to the multivariate logits. Derek Teather has since pointed out that it would have been better to assume a second order, rather than first order, process for the logits. In 1986, Marti et al used similar methodology to develop a method for the clinical evaluation of lymphocytosis. During the summer of 1971, I visited the American College Testing program (A.C.T) in Iowa City, stayed in the Students Union by the river for the first time, and wrote several A.C.T technical reports about my new approach to categorical data analysis.          While I was there, I met Jim Dickey who was visiting the University of Iowa from Buffalo. He was deeply philosophical and perceptive, and gave me lots of encouragement. A long friendship would ensue. Jim gave a seminar to the University of Iowa Statistics Department, about the scientific reporting of Bayesian posteriors, which he thought should be tracked against the prior. and I was very impressed by Chairman Bob Hogg’s good humour during the discussion. I was to visit A.C.T. again the next summer. While briefly collaborating with Jim Hickman, who was later to become Dean of Business in Madison, I told him about my new histogram smoothing method, which used an autoregressive prior process for the parameters of interest.  He and Bob Miller later applied similar ideas to Bayesian actuarial graduation in two impressive papers, and I was always very proud of this. [In June 1972, Jim and his wife took me to see West Branch, Iowa, the birthplace of President Herbert Hoover. And now, in 2012, Jim has sadly passed away in Madison, Wisconsin, aged 79. He was regarded as a great man in the area of the statistics of actuarial science, and his life and career should be celebrated] In 1984, Bob Miller and his student Bill Fortney were to express similar misgivings about the Lindley-Smith 1972 regression estimates to those that I discuss below. Bob and I sometimes had the same mindset about Bayesians who’re too religious. During the academic year 1971-2, I was, as a fully fledged Ph.D. student, permitted into our inner sanctum, the University College Statistics academic staff common room, every day for afternoon tea. I found the conversations there to be extremely stimulating and I still remember Mervyn Stone’s and Phil Dawid’s high quality humour, along with all of the Bayesian arrogance.          Egon Pearson, the son of the great Karl Pearson, occasionally appeared among the Bayesians. Neil Please, who organised STATLAB, usually slipped off after a single cup of tea.           Egon was an impressively tall and wise-sounding old man with white hair. I also liked Rodney Brooks, who had developed the pioneering Bayesian theory of Experimental Design, and Peter Freeman for his unique perceptions of life in general. [in 1976 Peter published a discussion paper in JRSSB about Alexander Thom’s megalithic yard. His Bayesian analysis of Thom’s prehistoric stone circle data was very well-received]. Meanwhile, Colin Stevens, an unsung hero who was visiting from I.C.I., was quietly developing a mixed model/ Kalman filter approach to Bayesian forecasting that he later published with the much-more-extrovert Jeff Harrison.          During that year, I prepared and taught a thirty-hour lecture course at City University, following in the footsteps of Adrian Smith, and I received the princely sum of £140 for my efforts. I also played football in the intramurals and scored a few goals, and played ping pong with Tony O’Hagan. Other friendly Ph.D. students at the time included Abimbola Sylvester Young from Sierra Leone, who was given his middle name by Jane Galbraith because she couldn’t pronounce his Christian name and was later a Chief of Statistics in Geneva, and Derek Teather who was to pursue an outstanding career in medical statistics. Jose Bernardo came later.          A number of leading international academics visited the department for long periods while I was a student there. These included Jim Zidek, Jim Press and Jim Dickey. Jim Bondar visited informally, and hung his coat in the student common room.     Jim Zidek     Tom with his father and stepmother outside his house on Pickford Street, Madison, Wisconsin in 1986.   Tom's inaugural lecture in 1996 as Chair of Statistics at the University of Edinburgh.  Vice Chancellor Sir Stewart Sutherland and Dean Geoffrey Boulton are in the foreground.   Tom with his co-author John Hsu and John's sons on Blackford Hill, Edinburgh in 1997.  The King's Buildings are in the background.     Tom Leonard - The Life of a Bayesian Boy       CHAPTER 4: THE UNIVERSITY OF WARWICK   Sylvia Richardson     Dr. A. O'Hagan   Dr. Tom Leonard   Dear Sir, I find Dr. Winnifrith's comments (see last issue of "News and Opinion") about the staff/student ratio of the Department of Statistics to be somewhat misleading.  The quotation "there are lies, damned lies, and statistics" arises because of the large number of non-statisticians dabbling with figures when they don't know how to interpret them properly!       Until 1975 we were one of the "small new developments" which Dr. Winnifrith is happy to excuse in his letter.  After the first intake of MORSE last year we have acquired an official staff/student ratio of 13.2:1 for 5 staff members and "roll-on" is likely to cause this to increase to about 20:1 by 1977/8 unless we obtain new staff appointments.       We are all naturally unsympathetic towards redundancies in any department. However, universities can only retain their prestige by supporting important new developments rather than pursuing a "lame duck" policy.  New courses can only be developed properly if appointments in fringe or unsuccessful departments are frozen, or if their staff are offered administrative duties to help their overworked colleagues in successful and relevant departments.   Tom Leonard Statistics   My very exciting times as a postgraduate student came to an abrupt end, largely because my wife was expecting our first baby. After being dined and wined by Jeff Harrison while he was still at I.C.I. in Cheshire, I was offered a lectureship at the University of Warwick, to start in September 1972. Before taking up the appointment I nevertheless visited Iowa City again in the forlorn hope of persuading A.C.T. to put my methodology into practice.          However, in June 1972 I learnt from my mother-in-law that my daughter had just been born in Wolverhampton two months prematurely and was surviving in an incubator. I promptly flew back to England, and soon afterwards Professor Harrison invited me to take up my appointment at Warwick straightaway (with a generous starting salary of £1935 per annum that was two points above the bottom of the scale). University College London was therefore suddenly largely a lingering memory and I was out in the Styx. [I returned to UCL in December 1973 for my oral, after my external examiner Patricia Altham had scrutinized my thesis. She asked lots of perceptive questions, and Dennis was keen to get her back on the train to Cambridge. My parents were absolutely delighted when I returned to Plymouth at Christmas as the family’s first doctor of philosophy] Jeff Harrison and Mervyn Stone are doubtlessly the two most perceptively intelligent people I have ever met. Perhaps Jeff will forgive me for reporting that during my first week at the University of Warwick (it’s built over former farmland on the southern edge of the City of Coventry), he fell into an eight-foot pit while walking across the mudflats on a campus where the white tiles were still falling onto the students and the Napoleonic Chancellor Jack Butterworth treated the junior academic staff  like guinea pigs.          Jeff redeemed himself during his second Statistics lecture at the university, by tossing a coin that landed on its edge on a shiny floor, and he celebrates this extremely unlikely event in his departmental history.  It was described as parapsychological by Alan Vaughan in his book Amazing Coincidences when the author was discussing my 1974 letter to The Times on the same topic. Soon after the coin tossing, Jeff was apprehended by Leamington Police on suspicion of smuggling forged bank notes from Belgium, but it was fortunately a question of mistaken identity and he was quickly released.  Robin Reed, a fellow undergraduate at Imperial College, and a talented probabilist, though never one to take the credit, was instrumental in helping Jeff and I to found the Statistics Department at Warwick. Robin is still there and, after Jeff’s retirement in 2000, he became the longest serving member in the department. I was saddened to see that Jeff’s official history of the department gives Robin and myself an honourable mention (just after the coin tossing) but scarcely acknowledges anybody else.       Jim Smith’s postscript to the official history is more generous but still fails to give more than passing credit to Keith Ord, Tony O’Hagan and Mike West each of whom moved on to high-flying careers at other universities (Penn State, Nottingham, and Duke), or to Sylvia Richardson. I always found the over-riding atmosphere in the department to be rather megalomaniacal, almost like a group psychosis.          Nevertheless, I revelled in Jim’s company when he was a Ph.D. student, I enjoyed played squash with Tony, and I found Keith and his wife, the American statistician Janice Derr, to be extremely hospitable and enjoyed playing scrabble with them. Jim wrote an outstanding thesis on Bayesian Catastrophe Theory and the Kalman Filter, nurtured by Jeff Harrison and under the eagle-eyed gaze of the all-consuming pure mathematician Christopher Zeeman (since elevated to greatness) who put Jim and Jeff in touch with the cusps and manifolds developed by Renée Thom. One of the problems facing Robin, Jeff and I was that the pure mathematicians regarded themselves as el supremos and all the other, supposedly inferior, branches of mathematics as student options. I therefore suggested formulating an alternative undergraduate degree in mathematics, and we developed a new degree called MORSE (Mathematics, Operational Research, Statistics and Economics) for undergraduates within our department. Robin Reed completed most of the spadework.          We originally wanted to include a colon instead of a comma after Mathematics, but the pure mathematicians fought this tooth and nail in the Senate in the so-called ‘Battle of the Colon’. I deserve credit for describing MORSE as an integrated single honours degree, and for devising the L-shaped corridor competition for our first pamphlet. I recall interviewing countless numbers of school kids and giving them guided tours around our still-muddy campus. We quickly achieved an intake (our very own) of over thirty students a year, and MORSE and MMORSE have grown from strength to strength ever since. An insightful student from Colombia called Isaac Dyner completed a Masters by research with me on a Bayesian topic. He is now a Professor of Operations Research at the University of Colombia.          I published several further papers out of my 1971Masters and 1973 Ph.D. theses, including: A. Bayesian Methods for Two-Way Contingency Tables (JRSSB , namely Journal of the Royal Statistical Society, Series B, 1975) that was published around the same time as Nan Laird’s Harvard Ph.D. thesis that addressed an Empirical Bayes approach to the same topic, which used her freshly developed version of the EM algorithm. While less general, Nan’s approach included superior, asymptotically consistent, estimators for the hyperparameters.          My paper included an analysis of Karl Pearson’s 14x14 social mobility table concerning the association between the occupations of fathers and their sons. An application of a four-fold exchangeability model lead to reduction to a quasi-independence model, and a convincing fit. Both Dennis Lindley and Henry Daniels were impressed by my practical example, and Irwin Guttman, who attended my 1975 University of London seminar while visiting from Toronto, thinks that it was the best thing that I’ve ever done. B. A Bayesian Approach to the Linear Model for Unequal Variances (Technometrics, 1975) The key idea here was to use a multivariate normal first stage distribution in the prior assessment, for the log-variances. After I taught this methodology to several animal science postgraduates attending my Statistics 775 graduate Bayesian course at Wisconsin during the1990s, it was applied by Tempelman, Foulley, Gianola and others to animal breeding (Rob Tempelman wrote his thesis on the topic before moving to Michigan State) and it is now an integral component of their literature. The time series special cases for the unreplicated model have been generalised and extended by several authors in econometrics, and my autoregressive process for the log-variances can be used to explain stochastically volatile data. [I once advised Nick Polson, while we were drinking together, that I discovered stochastic volatility, and he laughed his head off! Nick was also a wonderful gossip.]   Nick Polson    C. Some Alternative Approaches to Multi-Parameter Estimation (Biometrika, 1976). This paper quietly corrected my earlier work by incorporating better estimates for my hyperparameters leading to superior estimates for the first stage parameters, thus avoiding the ‘Lindley-Smith collapsing phenomenon’ (see below). [Perhaps I should call this the Lindley-Smith-Leonard collapsing phenomenon since it had been a feature of four of my previous papers. However, I was simply following orders, and Lindley and Smith have never corrected their estimation routines or retracted the key claims in their 1972 paper. There’s still time to do so, and I think they should. Early in 2012, Dennis published a very lucid letter in RSS News&Notes at age 85 in which he compared Bayesianism with Darwinism] Similar improvements are suggested in my paper A Bayesian Approach to the Bradley-Terry Model for Paired Comparisons (Biometrics, 1977), which was not part of my thesis work. However, the Biometrics paper was accepted by the editor Foster Cady primarily because he wished to publish Steve Fienberg’s numerical data relating to my ‘dominant and passive squirrel monkeys’ practical example. The approach can also be used to evaluate chess rankings, and the U.S. Chess Federation once showed some interest.          I moreover proposed convincing hierarchical Bayesian estimators, and also preliminary test estimators, in one-way ANOVA and multinomial contexts in my JRSSB (1976, with Keith Ord) and JASA (1977) articles, and obtained novel critical values for the F and chi-squared statistics .          Mervyn Stone gave me an unexpectedly bruising time as Editor of our JRSSB article while reducing it from a paper to a note. He subsequently contrasted our alternative to the F-test with his cross-validation procedures and with AIC, in his short paper in JRSSB (1977).          Hirotugu Akaike later advised me that my critical values were just modifications of his magical number 2. Mervyn didn’t like my uniform priors for the variance components, but they seemed pretty convincing to me. [Dennis Lindley had recently publicly recanted his previous advocacy of improper priors because he feared the Stone, Dawid and Zidek (JRSSB 1973) marginalization paradoxes. However this paradoxes only occur in pathological situations. Therefore, a general denunciation of improper priors wasn’t really appropriate.  Bayesian methods based on informative priors do frequently smooth away what the data are trying to tell you.] My method for the simultaneous estimation of the parameters of several multinomial distributions, which employed a Dirichlet-Dirichlet distribution in the prior assessment, only made it to Communications in Statistics (1977) since I couldn’t justify the posterior approximations well enough the convince JRSSB.          In my notes in Biometrika (1974) and Biometrika (1976, with Tony O’Hagan) I describe two different non-conjugate Bayesian estimation procedures for the location parameter of a normal distribution, which are readily generalisable to a broad range of models. When I first met up with Glen Meeden of the University of Iowa at Ames in 1978, he promptly identified me as ‘the guy who’d suggested that neat modification to the Bayes estimate for the mean of a normal distribution’. In 1971, I’d made my first ever contribution to the discussion of a paper read to the Royal Statistical Society (see Lindley and Smith, Bayes Estimates for the Linear Model, JRSSB, 1972) that addressed M-group regression, and also ridge estimators for a single multiple regression. The authors made the phenomenal claim that their shrinkage estimators for M-group regression led to 75% improved efficiency when compared with least squares. Indeed, the arch-frequentist Robin Plackett (erroneously) conceded when proposing the vote of thanks that the Bayesian estimates doubled the amount of information in the data. This was to lead to much wider acceptance of the Bayesian approach, which until then had been regarded as too subjective. I indicated in my contribution to the discussion that this methodology could be extended to the analysis of binomial, Poisson and multinomial data, using logistic, logarithmic and multivariate  logit transformations. I received a pat on my back from my supervisor for my efforts. However, my career suffered an unfortunately debilitating setback in 1973 when I published a dippy written contribution to Bradley Efron’s and Carl Morris’s paper Combining Several Possibly Related Estimation Problems, which they’d read to the Royal Statistical Society. Indeed, I inadvertedly exposed a flaw in the Lindley-Smith 1972 approach (e.g. Dennis’s and Adrian’s M-group regression estimates with unknown variance components collapsed towards each other much too readily).          Efron and Morris quite rightly jumped on all three of us during their published reply to the discussion and it became evident that the Lindley-Smith claim of 75% improved predictive efficiency was pie in the sky.     Bradley Efron   Carl Morris   It was not until 1984 that I learnt from Mel Novick in Iowa City that this brief written contribution, rather than personality issues (as suggested to me in 1981 by Bernie Silverman), was the real reason that my Ph.D. supervisor turned against me and became my ‘ripple from above’. (Dennis presumably thought that I was trying to expose himself and Adrian Smith on purpose. I suppose that I was, in subconscious terms, trying to get at the scientific truth. In those days I always thought backwards). In any case, Dennis’s negative attitude was to severely damage my career right into the 1990s, and even apparently influenced, via an indirect route, the tenure prospects of one of my former Ph.D. students. [Maybe it influenced my career until my early retirement in 2001]          It was not until 1987, when I chatted with Adrian at an ASA conference in San Francisco, that I was finally able to untangle all the scientific problems surrounding his 1972 approach (see also his 1973 papers in Biometrika and JRSSB). Adrian told me, after we’d downed a few drinks, that when he’d computed his Bayesian estimates as an over-enthusiastic student, he’d usually stopped after the first step of the iterations (these yielded quasi-Empirical Bayes estimates rather than the joint posterior modes), rather than converging to the theoretical solution, since that gave the practitioners what they really wanted. [One of Adrian’s former Ph.D. students once reported to me, during another drinking bout, that Adrian would blink quite persistently while his numerical iterations or MCMC simulations were wondering whether to converge. While this was doubtlessly just a flight of fancy, it did cause me to wonder a bit about Adrian.              Gelfand and Smith projected a version of MCMC (Markov Chain Monte Carlo) into the Bayesian literature in 1990 and this led to an enormous cottage industry. MCMC can be excellent for computing the marginal posterior densities of parameters in parsimonious models (but only by taking expectations of appropriate unnormalised conditional posterior densities) but not for calculating the posterior expectations of unbounded functions of the parameters. It has tempted many scientists to make their models far too complex, in which case the convergence can be abysmal. If your model overfits the data, then MCMC is unlikely to converge at all well] To add grist to the gander, the empirical validation of the Lindley-Smith estimates was flawed. It was performed at A.C.T. in Iowa City by three other authors, using Dennis’s earlier version of the estimates. This required a degrees of freedom prior parameter to be set to an arbitrarily small value.          According to Paul Jackson (personal communication), who found the situation to be extremely amusing, he [and maybe his co-authors, Novick and Thayer] instead carefully fixed the degrees of freedom to a value that was large enough to preclude the devastating effect of the Lindley-Smith joint posterior mode collapsing phenomenon and to yield excellent apparent predictive efficiency. Therefore the apparent empirical validation of the Lindley-Smith estimates, if they had been properly calculated, was based upon something entirely spurious.          These aspects were pursued by Irwin Guttman and his findings were published in JASA (Journal of the American Statistical Association), 1996, jointly with Sun, Hsu and myself; we showed, by using a limiting argument in a special case, that the Lindley-Smith estimates possess vastly inferior mean squared error problems [ whatever the values of their hyperparameters] when compared with ordinary least squares. Very similar problems hold for classical ridge regression i.e. the much-hyped Hoerl-Kennard ridge estimator is vastly inferior to least squares. In 1976, I made a contribution to the discussion of the Harrison-Stevens Royal Statistical Society read paper on Bayesian Forecasting where I described how their approach could be extended to non-linear situations using appropriate parametric transformations. Jeff Harrison paid scant attention to these ideas at the time, but Mike West took up the cudgel with some very sound technical work and published them jointly with Jeff  e.g. in their 1997 book Bayesian Forecasting and Dynamic Models.          Other Bayesian approaches to the forecasting of non-normal data are described in Ch.5 of my 1999 book Bayesian Methods, co-authored with John Hsu, and I remember developing a multivariate forecasting package for proportions of world sales of fibres that made I.C.I. very happy, for a much-needed £700. It was later neatened up by Trevor Gazard and reported, by Jeff, to the 1977 Royal Statistical Society conference in Manchester, and published in the conference’s proceedings. The forecasts varied according to the specification of a discount parameter, but Jeff took care of that. Later in 1977, I read a paper to the Royal Statistical Society in London entitled ‘Density Estimation, Stochastic Processes and Prior Information’. The vote of thanks was proposed by Peter Whittle and seconded by Bernie Silverman, and I was taken to dinner afterwards with the top brass of the society by its kindly president Professor John Kingman. The paper was well-received by a number of international scholars, and I felt that I had finally arrived.   Bernard Silverman F.R.S.            In my paper I tackled the long-unsolved problem of the non-linear prior-informative smoothing of a univariate density, by using a logistic density transform and an Ornstein-Uhlenbeck Gaussian prior process for its derivative, and this was effectively equivalent to non-linear smoothing method for a non-homogeneous Poisson Process. My assumptions lead to a non-linear fourth order differential equation for the posterior estimates, which I converted into a Fredholm integral equation. The solution was doubtlessly a spline and that seemed to please Grace Wahba.          I described several numerical examples, including an analysis of the flashing-green-man Pelican crossing data, and an analysis of Burch and Parson’s chondrite meteor data, that Jack Good later debated with me in JASA (1982).          Because of complex measure theoretic problems, I’d used a prior likelihood, rather than a strictly Bayesian approach, and the more religious Bayesians reacted to this technical detail with comical negativity. None of the Bayesian establishment turned up, and I’m still disappointed that they didn’t contribute to the discussion. [Fully Bayesian versions of this approach were later published in a series of papers (e.g. Biometrika 1991) by Peter J. Lenk of the University of Michigan School of Business, and by Daniel Thorburn of the University of Stockholm, with a variety of applications. Peter earned his tenure on the basis of these ideas. His 1984 Ph.D. thesis 'Bayesian non-parametric predictive distributions' (supervised by Bruce Hill) employed similar assumptions and won the 1985 Savage Prize.]   Peter Lenk   By this time, the departmental secretary at Warwick was feeling dissuaded from typing my papers and my name was being omitted from most of the department’s advertising. I was of course very perplexed as to why this was happening, since I had already made immense teaching, administrative and research contributions to the department, and was regarded, e.g. by Jeff Harrison, as a relatively nice person. Perhaps, in hindsight, it was a case of misdirected homophobia or maybe it was just a ripple from above.           I was in any case quite relieved when, following a visit to Warwick by Tom Stroud, his colleague Louis Broekhoven, the Director of the Statlab at Queen’s University, Kingston, Ontario, invited me to work with him and Dr. Jim Low of Kingston General Hospital for the first semester of my sabbatical year (1978-79). [Louis, who was Irish-Dutch-Canadian, had once worked in a group of postgraduates at UCL grinding out asymptotic expansions for Florence David, and he was a fine applied statistician too. He was promoted to full professor on the strength on his work with me.]     Isaac Dyner   Tom Leonard - The Life of a Bayesian Boy       CHAPTER 5: SABBATICAL YEAR (1978-79)       Queen's University, Kingston, Ontario   The University of Michigan at Ann Arbor   The University College of Wales, Aberystwyth     Gregynog Hall   Hotel Las Fuentes, Alcossebre   I was made very welcome by my hosts at Queen’s University, and soon felt at ease in both social and academic terms. Jim Low provided me with a retrospective data set that reported a number of variables for over two thousand mothers and their babies, the first large data set that I’d ever tried to analyse. The problem was to find the variables that best predicted a low measure of the acidosis in blood samples taken from the umbilical cords of the babies during labour. Babies with their measure of acidosis below a certain threshold were said to suffer from ‘fetal metabolic acidosis’ and this could give rise to serious post-natal problems.          I tried least squares multiple regression for a couple of months, but this invariably led to a remarkably poor fit, and values of R-squared alarmingly close to unity, as the data were so noisy. When everybody had given up on me, I therefore took the radical step for a Bayesian of resorting to data analysis. I tried splitting up the data into subsets according to different levels of gestational age. For each subset, I was subsequently inspired (divinely, or so I believed at the time) to split the data into three groups, corresponding to low, medium and high measures of acidosis. When I examined scatterplots of the birth-weights, I then discovered that, for each level of gestational age, the birth-weight distributions shifted sideways when moving along the three groups.          Imagine my excitement! I modelled each of the birth-weight distributions using a skewed normal distribution (originally proposed by Edgeworth (JRSSB, 1899), and reinvented by Ralph Bradley and then myself) and maximum likelihood/moment estimators for the three parameters. After an empirical application of Bayes theorem, I was then able to plot the probability of low acidosis against birth-weight at each level of gestational age.          With the exception of the overweight, overdue babies, the babies at greatest risk were those with low birth-weights, but when considered among babies of similar gestational age. No other variables seemed to affect this conclusion and I therefore refuted the medical folklore that was prevalent at the time; the three main predictors until then were totally useless, at least for the two thousand-or-so babies in that data set.          About 20% of the babies in the entire data set suffered from fetal metabolic acidosis. I therefore also reported ‘cross-over points’, namely the birth-weights below which my probabilities of low acidosis exceeded 20%. Jim Low took a brief look at the cross-over points and made a remarkable observation by reference to already published critical values for ‘intra-uterine growth retarded’ babies. The critical values were almost identical to my cross-over points, at each level of gestational age! We therefore arrived at a simple and scientifically validated conclusion; the babies at highest risk of fetal metabolic acidosis could be predicted by ultra-sound since these were the intra-uterine growth retarded babies. I’d also learnt that probabilistic prediction, rather than point prediction, can work best for noisy data sets. (perhaps more time series boffins should take heed of this!) Our conclusions were reported by Jim Low to a joint meeting of the American Obstetric and Gynaecological Societies and well-received, and they were published by several of us, with discussion, in the societies’ journal in 1983. When I presented them to a meeting of the Medical Section of the Royal Statistical Society in 1979, I started to receive some recognition in Britain as an all-round statistician. (Granville Tunnicliffe-Wilson, personal communication)   Dr. James Low Obstetrics and Gynaecology, Kingston General Hospital   When I was at Queen’s, I gave a number of well-received seminars around Ontario, and I continued my life-long friendship with (the highly-supportive Bayesian) Irwin Guttman while visiting the University of Toronto.  He frequently visited his buddy Norman Draper at the University of Wisconsin. [I visited Irwin at SUNY at Buffalo in 1992. We both helped his student Li Sun develop his thesis work on Laplacian approximations for random effects models, and Irwin later worked with me for several months at the University of Edinburgh]  I also visited Ann Arbor, Michigan, in 1978 to participate in one of Arnold Zellner’s NSF-NBER Bayesian Inference in Econometric and Statistics seminars , and I met Steve Fienberg (for the first time since a conference on categorical data analysis in Newcastle in 1975 ), Morry De Groot, Seymour Geisser, Bruce Hill and several other leading American Bayesians.          My talk on non-parametric Empirical Bayes and the Efron-Morris baseball batting example was well-received, and Arnold referred to it for long afterwards. My empirical Bayes procedures showed that the batters were divided into two groups, and that was probably because Efron and Morris had taken care to put two different types of batter into the same data set! I later published this analysis in Ann Inst Stat Math (1984).       Steve Fienberg   Arnold Zellner   Irwin Guttman            My friendship with Bruce Hill was to continue for a number of years even though we disagreed strongly about Bayesian coherence. At the 1979 Valencia conference, he announced during his talk that, ‘I’m looking forward to hearing from Professor Leonard why it’s good to be a sure loser’, but that didn’t deter us. While I was at Queen’s, I met up with the Dean of Engineering, David Bacon. David was one of George Box’s former students, and he wrote to George telling him about my successful medical data analysis. I was subsequently invited by Gouri Bhattacharyya to move to Madison, Wisconsin, where Norman Draper helped me to apply for my green card.            Despite my international successes, I received a torrid reception when I dropped by the University of Warwick early in 1979. I was therefore glad to retreat, albeit highly depressed, to the University College of Wales in Aberystwyth, where I spent the second semester of my sabbatical in the good company of Professor Jim Dickey, his wife Martha and his Welsh-speaking colleagues. [This was Dennis Lindley’s and Owen Davies’s former stomping ground, and I met Owen several times and went mountain-walking with him in his old age. He was a magnificent applied statistician and experimental design man out of I.C.I., and a predecessor of George Box] During that period, I stayed in a house previously owned by the historian R.F. Treharne and whiled away much of the time reading the classical detective novels that lined the walls in almost every room.          I also took time to revise my philosophies of statistics, in the light of my good experiences with the Ontario fetal metabolic acidosis data. It finally dawned upon me that the Bayesian approach is quite incomplete because it requires the mathematical and probabilistic specification of a sampling model, and cannot usually be used to derive suitably meaningful models from the data.          Moreover, Bayes factor methods for the comparison, or mixing, of several candidate models (or more recently when applied to forensic statistics) are usually quite worthless since they are subject to Lindley’s Paradox (see Dennis’s paper in Biometrika, 1957, that was published after his 1953 paper on unlikelihood but when he was still a diehard frequentist) and other curiously anomalous behaviour, including high sensitivity to perturbations in the prior distribution.          If information criteria are used for model comparison, then Akaike’s A.I.C. is more convincing than B.I.C., which is based on a very asymptotic approximation to a Bayes factor. However, A.I.C. is only tenuously Bayesian. An alternative called D.I.C. has more recently been proposed by David Spiegelhalter and others, and this approximates A.I.C. While D.I.C usually works well it is not, despite its elegant appearance, strictly speaking Bayesian or justifiable via probabilistic arguments.          It is consequently essential to separate inductive modelling, in relation to the data and the scientific or real-life background, from deductive inference and prediction, conditional on the choice of sampling model. George Box was at the time thinking along similar lines. Bayes would rule the roost if the sampling model were true. But, though some models are useful, most of them are either wrong or potentially inadequate. Dennis Lindley visited Aberystwyth for several days during that period and gave a seminar. Given my views on parsimonious statistical modelling, we were no longer seeing at all eye to eye, and I concluded that Dennis was keeping his blinkers on. He was indeed at the time advocating  L.J. Savage’s amazing philosophy that ‘a model should be as big as an elephant’, which is still misleading the economics profession and runs counter to the more generally accepted concept of parameter parsimony. [The problem with a large model that is too large is that its parameters can’t be well estimated from the data. Dennis always thought that Bayes took care of that. I prefer AIC and Jack Good’s ‘Occam’s razor’.         In 1983, I advocated the Savage elephant philosophy, on Dennis’s behalf, to the Cincinnati meeting of the American Statistical Association, while reading Dennis’s contribution, in his absence, to the discussion of a paper by Carl Morris. I created further general amusement by describing Americans as both fascists and colonials, also on Dennis’s behalf] While visiting Aberystwyth, Dennis kindly read a draft of my manuscript on fetal metabolic acidosis and concluded that my methodology amounted to ‘a good piece of data analysis, but not statistics’.  He also said that he always declined to consider any data set that couldn’t be analysed using a simple application of Bayes theorem.     16th August 2013: Please click on TONY O' HAGAN INTERVIEWS DENNIS LINDLEY for a very historical and illuminating Youtube video, This includes an account, at age 90, by Dennis of his time-honoured 'justifications' of the Bayesian paradigm, together with his totally unmerited attitude (since 1973) towards vague priors, including Sir Harold Jeffreys' celebrated invariance priors and Dennis's own student Jose Bernardo's much respected reference priors. I, quite frankly, find most of Dennis's opinions to be at best unfortunate and at worst completely ****** up, particularly in view of the highly paradoxical nature of the Savage axioms and the virtually tautologous properties of the De Finetti axioms as appropriately strengthened by Kraft, Pratt and Seidenberg (Ann. Math. Statist., 1959) and Villegas, Ann. Math. Statist (1964) [ See Fishburn (Statistical Science, 1986) for a discussion of the very complicated strong additivity and monotone continuity assumptions that are needed to imply countable additivity of the subjective probability measure]. His views on model construction demonstrate a lack of awareness of the true nature of applied statistics. He was however relatively recently awarded the Guy Medal in Gold by the Royal Statistical Society for his contributions. Dennis also confirms how he encouraged Florence David to leave UCL for California (he'd previously been a bit more explicit to me about this) and, quite remarkably, says that he tried to arrange the early retirement of two of his colleagues at UCL for not being sufficiently Bayesian!! This was around the time that he was influencing a downturn in my career at the University of Warwick. Dennis's account of his own early retirement does not match what actually happened. According to Adrian Smith, Dennis was encouraged to retire after a fight with the administrators over the skylight in Peter Freeman's office.       24th August 2013: Since studying the Dennis Lindley interview, I have debated the relevance of the Savage and extended De Finetti axioms with Professor Peter Wakker on the ISBA website. As a spin-off of this correspondence, I was contacted by Deborah Mayo, a Professor of Philosophy at Virginia Tech, who has proposed some counterexamples to Allan Birnbaum's 1962 justification of the Likelihood Principle via the Sufficiency Principle and Conditionality Principle. Her work may be accessed by clicking on: http://errorstatistics.com/2013/07/26/new-version-on-the-birnbaum-argument-for-the-slp-slides-for-jsm-talk/. I leave it to the readers to decide this controversial issue for themselves. I always thought that Birnbaum's proof was elegantly simple and completely watertight, and it would be quite amusing if I was wrong on this key issue. 26th August 2013:  I have now heard from Peter Wakker that Evans, Fraser, and Monette (Canadian Journal of Statistics, 1986) claim that the Likelihood Principle is a direct consequence of the Conditionality Principle, and that the Sufficiency Principle is not needed at all. Phew! There is clearly lots of room for further discussion. Some serious mathematical issues need to be resolved.   26th August 2013:  A RESOLUTION OF AN OLD CONTROVERSY   Michael Evans of the University of Toronto has just advised me that the proof of Birnbaum's 1962 theorem is not mathematically watertight. It should be correctly stated as follows: Theorem: If we accept SP and accept CP, and we accept all the 'equivalences' generated jointly with these principles, then we must accept LP. He also proves: Theorem: If we accept CP and we accept all the equivalences generated by CP then we must accept LP.   Furthermore, it is unclear how one justifies the additional hypotheses that are required to obtain LP.  Michael believes that Deborah Mayo's counterarguments are appropriate. History has been made!   Shucks, Dennis! Where does that put the mathematical foundations of the Bayesian paradigm? Both De Finetti and Birnbaum have misled us with technically unsound proofs. I should have listened to George Barnard in 1981.   While Professor Mayo's ongoing campaign against LP would appear to be wild and footloose, she has certainly shaken up the Bayesian Establishment.   Deborah Mayo     While I was at Aberystwyth, I was invited to participate in the annual Statistics at Gregynog, a rare honour. The speakers presented their papers in an archaic building with a croquet lawn, which Bradley Efron once described as ‘that nice country house just outside London’. I met Ralph Bradley, who’d just finished a nineteen-year stint as Head of Statistics at Florida State University. He explained the origins of the skewed normal distribution to me. During this period, I received my eagerly anticipated offer from Gouri Bhattacharyya, the Chairman of Statistics at Wisconsin. One year (1979-1980) as a visiting Associate Professor (for the princely salary of $22000 that almost tripled my stipend at Warwick) followed by a permanent appointment as soon as my tenure could be finalised. Both appointments were initially half-time in Statistics and half-time in the Mathematics Research Center, which was housed on the edge of the campus in the fourteen-storey WARF building and funded by the US Army. [MRC had been blown up in Sterling Hall during the Vietnam War when the protesting students were being chased with tear gas around the city]   The Queen and Castle pub in Kenilworth   I felt bad about leaving my recently-purchased house near Kenilworth Castle, but felt forced to do this because of the bizarre situation at the University of Warwick. Indeed, in later years the influential Bayesian group there was dismantled when two world-leading Bayesians were denied their well-deserved promotions. It was only Jim Smith’s return from University College London that restored any sanity to the situation. During my sabbatical semester in Aberystwyth, I was delighted to receive an invitation from Jose Bernardo (an outstanding practical Bayesian if ever there was one) to present a discussion paper during June 1979 at the first of the long series of Bayesian Statistics conferences to be organized by the University of Valencia.          While I was preparing my Valencia conference paper ‘The roles of inductive modelling and coherence in Bayesian Statistics,’ my only objective was to discern scientific truth, rather than to attack the high priests of the Bayesian establishment. I however clarified in my mind that the De Finetti and Savage axiom systems, which were supposed to justify Bayesian inference and decision-making, were at best tautologous with their specific theoretical conclusions and at worst downright misleading.          Moreover, to insist that a statistician should be ‘coherent’ and Bayesian, when choosing his sampling model in relation to the scientific background, was totally out of line, as well as completely impractical. The ‘sure thing principle’, which requires a decision-maker to maximise his average long term expected utility, is absolute bullshit. For example, most mortals need to hedge against catastrophic losses and others wish to maximise the probability of a certain monetary gain. [See Leonard and Hsu, Bayesian Methods, 1999, Ch.4] The first Bayesian Valencia conference, at the Hotel Las Fuentes on the Mediterranean coast between Valencia and Barcelona, was a wonderfully iconic event; I for example met Jack Good, Art Dempster, Hiro Akaike and George Box for the first time. George and I went swimming in the bay together, and Jeff Harrison and I talked about synchronicity with Jack Good on the end of the pier. I therefore initially  took it as a joke when Adrian advised me that ‘I would be destroyed by the storm that hit me’. I have nevertheless felt disturbed by this warning ever since. I was impressed by Steve Fienberg’s discussion of Jeff Harrison’s paper on Bayesian Catastrophe Theory and, while Jeff seemed to regard it as a catastrophe, I was glad to renew my friendship with Steve. [I last met Steve at the 2002 RSS Conference at the University of Plymouth, after my early retirement, but I haven’t been particularly active in Statistics since, apart from helping John Hsu to complete Bayesian Methods in Finance with Rachev et al, and Bishop Brian of Edinburgh with his Diocesan accounts. The conference dinner was held in the great barn at Buckland Abbey on Dartmoor, and that was also the last time I talked to Peter Green. Terry Speed, who was a defence expert witness in the O.J. Simpson case, and I discussed the merits of being honest and emphasising the truth, in the context of DNA profiling. Bruce Weir, the prosecution expert witness during the O.J. Simpson trial, had screwed up on the arithmetic. The British Forensic Science Service could also learn a thing or two from Terry] The paper that I’d prepared in Aberystwyth was well received at Valencia 1 (e.g. by Jim Dickey, Bill DuMouchel and Jay Kadane), since most of the Bayesians in the audience were also pragmatic statisticians, and I was undeterred when Dennis and a couple of heavily-axiomatized discussants made some unnecessarily angry, and rather puerile, comments regarding my views on the notion of coherence.          While the paper, that attempted to inject more practicality into applications of the Bayesian paradigm, is seldom cited, I am advised by Mark Steel and Deborah Ashby (personal communication) that it is known to the next generation of Bayesians and has influenced their thinking.     Mark Steel   Deborah Ashby   I drank far too many cointreaus during the final dinner, while George Box and Herb Solomon were singing ‘Our Theorem is Bayes Theorem’, and I puked the seafood up all over the beach. I was deeply saddened to learn, in hindsight, that I had been ferociously stabbed in the back by two leading Bayesians (not including Adrian), who tried to block my escape route to the University of Wisconsin, presumably so that I could wither away promotionless at Warwick.  Dennis has since corroborated this, and Adrian’s dire prophecy was almost correct.   Bayesians at Play (archived from Brad Carlin's Collection)            John Deely, a wonderfully honest and perceptive gentleman from Christchurch, has since let a cat out of the bag by advising me that Dennis and Adrian would after that usually ice me out of the conversation, and respond as if I didn’t exist, whenever he tried to talk to them about me. John called this ‘the Tom Leonard mystery’.   John Deely   Nevertheless, Dennis did express his admiration to John on one occasion about my quick and easy derivation of his, and Adrian’s, M-group regression estimates, that cut out a great deal of extraneous matrix algebra. I’d completed this derivation off the top of my head for Dennis just before the presentation of their paper to the Royal Statistical Society when he couldn’t remember where their formula for the pooled regression came from. Jim Smith advised me much later that Adrian had told him that he had absolutely nothing against me apart from ‘a slight problem when we were students’. Perhaps this was because I’d admired Adrian so much, as God’s perfect creation. Dennis certainly did so too. It’s not every supervisor who would’ve helped his student so much.     Tom Leonard - The Life of a Bayesian Boy       CHAPTER 6: THE UNIVERSITY OF WISCONSIN-MADISON   Painting of The Mayflower Rose by Fabio Cunha   In what wondrous dream Do I suppose I met the Mayflower Rose? Her petals turned to pink In a hug and a blink; Her stem twisted in the breeze When I fell to my knees; Her aura turned heavenly and angelic As I plied her with Dumnonian magic. But when the prickly thistle flew in, Rose was gone in the din. I twisted and turned, As I drank like a tank for ever and a day. When Yank fought Assyrian in the Gulf of Tears, She, the Voice behind the Screen, Spoke as if I’d never been. Now she beams across the mind waves In my wondrous dreams.   © Thomas Hoskyns Leonard, January 2013         George E.P. Box   Grace Wahba   Richard A. Johnson   James Hickman (1927-2006)         Kam Wah Tsui   Brian Yandell   Murray Clayton   Sue Leurgans   A Statistics Department Faculty Skit Madison, Wisconsin, Christmas, 1983 The participants are Richard Johnson, Grace Wahba, George Box, Tom Leonard, Tim Reed, and John Gurland.   A Statistics Department student skit in about Christmas 1990 Tom is played by Joanne Wendelberger, waking up during a seminar and uttering some totally irrelevant pearls of wisdom about the Bayesian approach.   Tom's Facebook friend Bob Wardrop with his three grandchildren, Lodi, Wisconsin, 2013     I hurriedly left a family holiday in Tenby in August 1979 when my U.S. visa came through, and received a warm welcome from George and Joan Box in Madison, where I  befriended Rich Johnson, Jerry Klotz, Grace Wahba, George Tiao, Sue Leurgans and the Statistics Department Associate Chairman Bob Wardrop.          Joan Box was Sir Ronald Fisher’s daughter, and the authoress of R.A. Fisher,  the Life of a Scientist. George’s two youngest children were Sir Ronald Fisher’s grandchildren, and I got on well with Harry.            George told me numerous amusing tales e.g. about what happened when John Tukey visited Fisher for tea, and how Florence David had once declared, “Don’t get into my car, George Box!” after George had criticized one of her more boring presentations to the Royal Statistical Society. During my first semester, I taught Statistics 775, a graduate course on Bayesian decision theory, and Wing Wong was my most brilliant student. In the 50th Anniversary history of the department, Norman Draper, Steve Stigler et al were to much later highlight my teaching and research in Bayesian statistics in generous terms  (I also taught 853 Bayesian Inference), together with further contributions to the Bayesian cause by Kam Wah Tsui and Michael Newton.          During the years that I taught Statistics 775, I was to have the privilege of awarding A grades to a number of subsequently distinguished statisticians, including Sharon Lohr, Dennis Lin, Finbarr O’Sullivan and KyungMann Kim. When I was Chairman of Awards, I appointed Dennis, whose financial support wasn’t guaranteed, to his first TA-ship, after he’d marched bravely into my office. He probably never knew what thin ice he was treading on.          I was to be an active member of more Ph.D. committees than I can remember. I, for example, made substantive contributions to a number of Grace Wahba’s students’ theses, and several others.   Doug Nychka Neil Gandal Finbarr O'Sullivan Jim Wendelberger Joanne Wendelberger   Jan Ondrich (Economics) and family   POSTSCRIPT TO LIFE STORY            I conclude my life story on 6th April 2021, largely physically incapacitated by my chest problems, but more mentally alert than ever. I finally returned to the University of Warwick in August 2017, after 38 years to attend a Quakers Annual Meeting. But late in 2017, I suffered two serious falls which damaged my left leg. I nevertheless celebrated my 70 th birthday in Vittoria Restaurant on 24th March 2018, with 37 guests including John and Serene Hsu from Santa Barbara, and Diego and Diane Perez from Manchester.          In July 2019, I returned from UCL after almost 50 years to give evidence with my flatmate Scott Forster, as expert witnesses to the Commission of Inquiry into the History of Eugenics at UCL. It was good to meet Professor Tom Fearn once again, and our verbal and written submissions were well received. I was delighted to learn during January 2021 about the sweeping decisions made by UCL based on the Commission's recommendations,          I'm still living in my flat in Broughton, Central Edinburgh after over 22 years, and trying to survive the pandemic. I stopped attending the Quakers during November 2019, some of them sided with TERFs. rather than trans people, and I now attend my all-accepting parish church, Broughton St. Mary's, e.g. by Zoom From the Archives of the Mathematisches Forchungsinstitut Oberwolfach Elizabeth Rose Sanders is the fourth mathematician from the left   As part of my duties at the Math Research Center, I taught several short courses on Statistics and Experimental Design at military bases around the US, including the space station in Huntsville, Alabama, with the late Toby Mitchell who was visiting from the Oak Ridge National Laboratory in Tennessee and ran for miles every day to keep himself fit. Toby was very supportive and introduced me to the key statistical concept ‘the greater the amount of information the less you actually know’ when justifying randomization at the design stage, a concept totally alien to diehard Bayesians.   Tom's colleague Toby J. Mitchell (d 1993). Tom and Toby taught Statistics courses at US Military Bases and the  space station in Huntsville Alabama, together, and visited Washington D.C. from Adelphi, Maryland in 1980.   So everything was going perfectly (I remember going swimming in Lake Mendota in late October). I was successful at tournament chess (for example beating the mathematician H.J. Keisler in 19 moves in a chess miniature subsequently published in a book about the Caro-Kann defence) and began to recover from my previous academic misfortunes. But catastrophe struck just before Christmas 1979. Following the machinations of a ruthlessly ambitious untenured assistant professor, and a weird reference request, I was attacked in the most vitriolic terms by the British Bayesian establishment, and my prospects of tenure at Wisconsin were placed in the most serious doubt.          George Box and George Tiao gave me considerable support during the traumas that followed and, rather than being sent packing, I was, to my surprise, offered tenure early in 1980. However, in the meantime I lost much of my self-credibility. During my rebuilding process, I was able to create excellent ties with Arnold Zellner, a distinguished professor in the Graduate School of Business at the University of Chicago. Over the years, I was to attend and contribute a number of presentations to his twice-yearly series of Bayesian Inference in Econometrics and Statistics seminars. When I helped organize one in Madison in 1984, Jim Berger and his cronies stayed drinking into the wee small hours after a party in my house.   Jim Berger            Then, in 1993, I helped Arnold to devise and found ISBA, the since highly successful International Society for Bayesian Analysis, and I give myself credit for choosing its name. He was the first president, and I was the first newsletter editor and a member of the Constitutional Board. There is a picture of us on the Internet, taken in the Hotel Nikko in San Francisco, that impressed my older daughter.          Arnold is perhaps the person who has supported me most of all in academia. He once described me as ‘light on luggage but heavy on ideas’. He encouraged my efforts during the early 1980’s to investigate alternatives to expected utility theory (see Ch. 4. of Bayesian Methods by Leonard and Hsu, which was not published until 1999) that could in principle be used by the banks to extract more profits from their customers when selling portfolios. From 1980, I also benefited from my friendship with Jan Ondrich, a chess-playing graduate Economics student from Toronto. I helped him with some of the Bayesian aspects of his research and he moved on to become a professor at Syracuse. Not to forget Elizabeth Rose Sanders from Penn State, who was to earn her doctorate with Norman Draper before joining the C.I.A. in Washington. Jan and Betsy taught me more things about academic politics and international academia than I had ever comprehended. I nevertheless persisted until my retirement with the foolish notion that ‘life is too short to be politically expedient’.  I also enjoyed my friendship with Neil Gandal, the captain of the Statistics Department soccer team, for which I also played near Shorewood Hills, a charming fellow who would later become a professor in Tel Aviv after obtaining a Ph.D. in Economics in California. During 1980, George Box and I planned his exorbitantly expensive and much-vaunted special year at the Math Research Center on ‘Scientific Inference, Data Analysis, and Robustness,’ with the help of C.F.Wu. The idea was to invite a number of statisticians to visit the center during the year, and to ask everybody to come back and attend a conference in December 1981.          The conference proceedings were later published by Academic Press in a volume edited by Box, Leonard, and Wu. The overall conclusions quite predictably supported George’s and my thesis (e.g. at Valencia 1) that the Bayesian paradigm is good for inference but not for modelling. So everything was going well for me once again. But, at the beginning of 1981, disaster struck one more time. George had emptied his (or rather the military’s) coffers to invite Dennis Lindley to Madison as one of the key participants in the special year, because he wished to debate the fundamental philosophical issues of Statistics with him. George said that he also wished to offer Dennis the hand of friendship after a feud that had persisted ever since George’s international divorce while at Princeton during the late1950’s (that Dennis regarded as illegal!), since it was better for us all to be one big happy family.          However, shortly before his arrival in Madison in January 1981, Dennis wrote to George accusing me of having read ‘his letter of reference’ during my tenure process. This was pure paranoia, because even I wasn’t quite dumb enough to have asked Dennis for a reference and I’d never even known that he’d written a letter about me to Wisconsin, let alone a letter that hadn’t been officially solicited. Adrian had warned me off several years previously when I wasn’t appointed to a Fellowship at Oxford after Dennis had keenly agreed to be a referee and then advised me that I was well-favoured for the position. That had already made me wonder about Dennis.          George gave me enough information to conclude that Dennis was responsible for most of the vitriol in late 1979, that had almost denied me tenure and sent me back to Warwick. This, quite surprisingly, came as a big surprise. Things did not go well between me and  Dennis after his arrival, particularly when he admitted to having attacked my career for the previous eight years, and moreover brought my erstwhile departmental chairman Jeff Harrison back into the equation, (after playing silly buggars over Marie Johnson’s reluctance to give him a parking permit and refusing to turn up at MRC).          I responded to Dennis much too wimpily and promptly experienced a frightening mental breakdown during a fit of anger in my flat on University Avenue, and ended up in Emergency at UW Hospitals and Clinics. Until that time, my ‘fogginess’ was caused by my obstructive sleep apnoea (nowadays I sleep with an APAP machine since I would otherwise choke every fifty seconds), but I now exhibited more serious symptoms. My health was not to improve for several years and I did not properly recover my cognition until some time after my divorce in 1984. In hindsight, the break-up of my marriage and the severe downturn in my career seem to have been largely caused by infighting between other statisticians. Perhaps I and my lovely family were pawns in a chess game between the gods. During his semester-long 1981 visit, Dennis described George to me as ‘pure evil’ since he thought George was ignoring him!! Other people thought that Dennis was playing the role of punch bag. Dennis did offer to recommend me for the chair at Manchester, but I gracefully declined. Around that time, Chen Wen Chen, a brave Han Chinese assistant professor at Carnegie-Mellon was axed to death by the Taiwanese secret police and left on the campus of the University of Tapei [this was confirmed by Morry De Groot when he visited Tapei with an ASA delegation, but the Associated Press reporter Tina Chou was blackballed by the Taiwanese authorities for long afterwards. Wen’s death has since been established as a seminal event in the history of Taiwan].   Morris De Groot (1931-1989)            This scenario added to my discomfort and made me feel quite insecure, since I believed, correctly or otherwise, that Wen’s misfortunes were slightly related to my own (i.e. that there was a common factor in American academia). I was to receive an unexpected email during the 1990s that confirmed my suspicions. The intrigues were certainly well understood by a selection committee for the Chancellorship of the University of Taiwan. I first learnt, in 1981, about the academic intrigues surrounding Wen's murder when one of my teaching assistants at Wisconsin was cruelly and quite unfairly bad-mouthed to a senior faculty member. One of my first sources of information was a highly respected Chinese professor of mathematics at Penn State. The Sino-American academic intrigues in the United States that may have led to Wen’s death are alluded to in Chapters 11 and 20 of my novel Grand Schemes on Qinsatorix [where Fleance leads a rebellion of the golden-skinned Icarians following his brothers’ deaths and his persecution by the ‘Admiral’]. My sources of information are clarified in detail in the Author's Notes preceding my novel, though a couple of my senior colleagues at Wisconsin remain anonymous.   Chen Wen Chen (1950 - 1981) Han Chinese Martyr   My best memories of MRC’s special year are walking across campus with Hiro Akaike, watching several episodes of Brideshead Revisited with Mike Titterington and his wife in their apartment in University Houses, climbing the post-ice-age cliffs at Devil’s Point with Mike, and with Phil Dawid, and lunchtime conversations with Michael Goldstein and Peter Green.   Hirotugu Akaike            Granville Tunnicliffe-Wilson visited with his family sometime afterwards from the University of Lancaster. We went swimming together and developed a long-lasting acquaintanceship. I talked at length to him at an RRS Environmental Statistics Meeting in Edinburgh in 2002, when the speaker turned up a couple of hours late.     Granville Tunnicliffe-Wilson   Peter Green   Although I was spaced-out and anti-social for most of the 1981 special year, I managed to develop a conditional Laplacian approximation to predictive and marginal distributions, via a backwards application of Bayes Theorem, very essentially after using a preliminary normalising parametric transformation. (a device ignored by numerous later authors). This was published in my short note in JASA (1982) and by Leonard and Novick (Journal of Educational Statistics, 1986).  It predated efforts by Kass,Tierney and Kadane, who obtained asymptotic saddle-point accuracy but did not typically apply their approximations in a manner which would ensure the excellent finite-sample-size numerical accuracy observed by John Hsu in his Ph.D. thesis, and by Leonard, Hsu and Tsui (JASA, 1989) I breathed a sigh of relief when Dennis Lindley decided, for reasons best known to himself, not to return to Madison for the, highly successful, December 1981 conference on Scientific Inference, Data Analysis and Robustness, as agreed. George Box promptly declared victory since he felt that Dennis had ducked out of a possibly embarrassing intellectual debate.          I recall being soundly told off at the conference by George Barnard for my positive interpretation of Birnbaum’s 1962 justification of the Likelihood Principle, a viewpoint so convincingly taught to me by Phil Dawid and which Jim Berger has advocated in his monographs ever since.          Bob Hogg was much more supportive e.g. about my proposed inductive procedures for model selection, and that was to lead to even further intrigue the following year when he used them to tease Dennis’s erstwhile ‘sugar daddy’ Mel Novick in Iowa City. I’m glad that I left the U.S. Army’s Math Research Center in 1983; the director had been trying to coerce me into working (along with C.F.Wu, who was much more dedicated to the cause and developed some outstanding theoretical results), on a thinly-disguised experimental design problem that turned out to relate to the optimal way to aim nuclear missiles at silos. [To my shame I did publish a couple of MRC technical reports on the topic (including An Inferential Approach to Quantal Response, MRC Technical Report, 1982) and I asked my project assistant Michael Hamada to do a few simulations. The idea was to base the choice of the design measure on the posterior density of the effective dose. In 1996, I published these ideas with John Hsu, totally disguised and with due acknowledgement, in a paper on biossay in Modeling and Prediction : Honoring Seymour Geisser. But my ideas were, as far as I know, never implemented by the military.          Michael Hamada is now a highly-accomplished statistician at the Los Alamos National Laboratory in New Mexico. He has published a prestigious book on the Design of Experiments with C.F.Wu.] I have all sorts of other fascinating stories to tell e.g. during one consultancy we were advised that the military would fire three Pershing missiles each time they tested them since they needed to keep three departments happy.          A statistical conference that George and I attended in the Naval Postgraduate School in Monterey, California was hijacked by several generals, one of whom declared that ‘a small amount of brutishness is worth lots of pity’. Bradley Efron expressed his dismay when he got to present his paper about the bootstrap. To his enormous credit, George, who benefited from hefty grants from the military for purely academic research, had once told them to go forth and multiply, or words to that effect, when they tried to take him up in a helicopter to review the troops. When the generals persisted in controlling the Monterey conference, he took us for a walk along the beach. [The totally fictional character Professor Brad Redfoot in my novel Grand Schemes on Qinsatorix is very slightly motivated by George. The campus of the University of the Sunrise in Trivoli is modelled on the campus of the University of Wisconsin-Madison] MRC’s total disregard for Wisconsin State Law (by not focusing on purely academic  research) was to lead to its final demise during the Gulf War in 1991 after the students on campus got wind of the less salubrious activities and protested to Chancellor Donna Shalala. I’m still trying to track down an article I published in The Daily Cardinal. I do recall Rich Johnson’s reaction to reading a stray copy of the article, and a graduate student from another department using my revelations as the basis for his detailed report on the controversy.            Rich told Jerry Klotz and me later, during one of his informative lunch-time conversations, that John Nohel, the long-time Director of MRC, had been dragged out of bed to explain himself on these issues. As my colleague Bob Miller so aptly remarked ‘it couldn’t have happened to a nicer person’. Now Bob was a gentleman! Before I left MRC in 1983, I used the expertise there (Ben Noble, Dennis Cox, and an intensely theoretical Jewish visitor whose name I cannot recall) to formulate a new Bayesian approach to the estimation of a covariance matrix, using a matrix logarithmic transformation and a multivariate normal prior. The prior to posterior analysis was virtually impossible and I needed to refer to a Volterra integral equation. (Dennis also advised me regarding the Statistics of Paternity Testing, and this was to get me into numerous Mid-West court cases.)   Dennis D. Cox   Because of my health problems, I wasn’t able to take any credit for this until much later, and a number of other potentially successful projects went by the wayside. Brian Yandell and Tim Read, both assistant professors, were two of my drinking companions around that time, and I remember both of them on one occasion becoming quite convivial. Brian was more recently appointed Chairman of Statistics, but handsome Tim (who’d published with Noel Cressie and worked in Biostatistics with David De Mets) disappeared and I haven’t been able to trace him since. Maybe I yearn for too many lost friendships. Where is everybody now?     17th July 2013:  An e-mail from Tim Read Hi Tom!   Great to hear from you after so long and to hear you are doing well!  I enjoyed seeing the pictures and reading your web-page which brought back a flood of memories from those years!  I have attached a more recent picture so you can see the effect of time.   After leaving Wisconsin in '84, I went to work for Hewlett-Packard in the Bay Area at their Stanford Park Division.  After 4 years, it was time for a change and I went on a one-year backpacking trip with my wife across Africa and much of Asia which was a life-changing experience.  On our return to the US at the end of '89, I went to work with DuPont in Wilmington, Delaware where I remain to this day ... something I never expected, however the work has been interesting and diverse, including 6 years developing teams back in Asia (Singapore and Shanghai).  Currently I am working with our new Biotechnology R&D organization based in California, lots of interesting challenges and lots of cross-country red-eye flights for the time being...  Wishing you all the best for the future and thanks for getting in touch! Tim Read     Tim Read  (thirty years later!)   David De Mets was perhaps the most actively political academic I’ve ever met, and that’s saying something. He reportedly kept private files on every member of the Statistics department in his office. But he was able to build a prestigious Biostatistics empire in the Medical School, albeit at a human price, with outstanding creative research and medical consultative contributions from the likes of Rick Chappell. Michael Newton and Kyung Mann Kim. David’s own research was a bit on the dry side. [The Fundamentals of Clinical Trials? Isn’t that pie in the sky? It’s impossible to sufficiently replicate statistical experiments in medicine, and large enough sample sample sizes for practical significance and effective randomization are usually well nigh impossible in situations where objective conclusions are sought after.] Around this time, Taskin Atilgan from Izmir developed an empirical model selection criterion EIC with me, which referred to the ridge that appears on graphical plots of the log-likelihoods of nested models. While EIC wasn’t quick-and-easy, it compared well in empirical studies with both AIC and BIC. Taskin worked and published, on the side, on tRNA sequences in bacteriology. He also published several joint papers out of his thesis, including one with me (in 1987) on penalized likelihood procedures for smooth bivariate density estimation, after moving on to Bell Labs. During his Ph.D. celebrations in 1983 almost the entire Turkish community of Madison partied in my house. During 1982, Bob Hogg, who’d listened in awe to my presentation at the December 1981 MRC conference in Madison, invited me to visit the University of Iowa to give a seminar on my views about Bayesian coherence. He was a most hospital host, before vanishing before dinner to watch a basketball game. Unfortunately, my old friend Mel Novick was suffering from an unexpected heart attack at the time, and wasn’t able to attend my seminar as he’d planned. The next morning, Bob quickly sent me packing back to Madison, and I was rather slow on the uptake in realising why. My step mother was later most appalled to hear this academic story, and I feel bad about it too. I visited Iowa City for a fourth time during the Summer of 1984, and spent three months at the Lindquist Center for Measurement with Mel, with whom I’d worked at the American College Testing Program in 1971 and 1972 when I was a student, and he’d taken me out for enormous meals. While he’d never encouraged me to publish my research with him, he implemented some of the suggestions in my five A.C.T. technical reports in a 1975 paper in Psychometrika that earned Charlie Lewis his tenure. Maybe that was fair. Mel paid me a total of $1200 for my efforts, and they did reference one of my technical reports, but Ming-Mei Wang put the paper together. Maybe Mel and Charlie chose the numerical example.   [Mel had made himself famous at the Educational Testing Service in Princeton in 1967 by publishing the seminal text Statistical Theories of Mental Test Scores with Frank Lord, but with magnificent contributions by Allan Birnbaum who was shamefully dropped by Lord as a co-author and didn’t bother to check the proofs. While  Mel was Dennis Lindley’s erstwhile long-term ‘sugar daddy’, he’d fallen out with him in 1981 over something or other. Irwin Guttman once explained Mel’s more general psychology to me by describing him as ‘the fat boy on the block’] However, I was delighted, in1984, to receive three months salary out of Mel’s enormous ONR grant, since I would have otherwise been skint.          During my stay, in an office behind the celebrated ‘Bayes barrier’, I was to complete some interesting research with Mel on Bayesian Full Rank Marginalization for Two-Way Contingency Tables, which he insisted on publishing in The Journal of Educational Statistics (1986), even though the referee thought that it was of high enough quality for JASA. The JES paper includes our analysis of the Marine Corps Data, where we were able to combine our new theory with statistical modelling in relation to the data and scientific background, in order to partition and collapse the table. This analysis was favourably discussed following a seminal paper on the chi-squared statistic in the Annals of Statistics (1985) by Efron and Morris. Brad and Carl compared my approach with their own.   I also helped Mel and a his hard-working Ph.D. student Shin Ichi Makeyewa to develop an Empirical Bayes approach to factor analysis, using shrinkage estimators for the variances, and this seemed to work well in practice since it avoided the anomalies (e.g. factor loadings close to zero) of maximum likelihood.  I guess that it’s been published somewhere too, and I’m still hoping that I was a co-author.          Mei-Ming Wang was a chatterbox. She told me that when Mel was editor of The Journal of Educational Statistics, the material in some of the rejected papers got published by other authors, but I have no way of ascertaining whether she was correct. During my 1971, 1972 and 1984 visits to Iowa City, I sketched out several new hierarchical Bayesian approaches to Item Response Theory. [e.g. ONR Technical Report 85-5, 1985, has, according to my records, been cited in the psychometrics literature, by Robert J. Mislevy of E.T.S. and others, as a major treatise on Birnbaum’s two-parameter logistic model] In 1994, I was to co-author a paper in Psychometrika on this topic with Frank Baker and Seock-Ho Kim of the University of Wisconsin, after helping Kim to complete his Ph.D. thesis in Educational Psychology. In 1991, I’d published another paper in Psychometrika, with John Hsu and Kam Wah Tsui and concerning extra-binomial variation alternatives to the beta-binomial model. Maybe I’m a psychometrician by trade. I’m currently working on more math for the two-parameter normal ogive model, in an attempt to pragmatise Jim Albert’s prior-informative MCMC approach. Kim has recently written a book with Frank Baker, also on Item Response Theory, and he is now a prize-winning Professor of Educational Psychology at the University of Georgia.   Seock-Ho Kim   During the Summer of 1984, Mel and I visited the Educational Testing Service’s Frank Lloyd Wright building in Princeton. We were met by a hostile Frank Lord and I learnt how the Office of Naval Research doled out its enormous grants to the psychometrics profession. This was not purely on merit. When I returned to Madison in the Fall of 1984, I became depressed again and my career seemed to relapse into its previous unproductive turmoil. However, my colleague Kam Wah Tsui helped me in two different ways during 1985. Firstly, Kam encouraged me in my renewed spiritual beliefs. While Blackhawk Evangelical Free Church wasn’t exactly perfect for a free thinker like myself, the activities there helped me to build up my self-esteem during the next seven years, and I taught Sunday School for some time. But the wolf seemed to throw off its sheeps’ clothing during Bill Clinton’s presidential election year. The broadly-defined ‘Campus group’ met for bible readings in my house on Pickford Street and all sorts of real-life experiences, including shootings in Texas, were discussed. Blackhawk expanded rapidly during the conservative backlash in Madison, and now has several thousand zealous members. Maybe Chief Blackhawk of the Sauk is turning in his grave. Kam also persuaded me to suggest a research problem for his beginning Ph.D. student John S.J. Hsu, and we proceeded to effectively jointly supervise him. It was John who first demonstrated the excellent numerical accuracy of sensibly-formulated conditional Laplacian approximations (Leonard, JASA 1982), an accuracy that continued right down the tails of the approximate marginal posterior densities. A generalisation to approximations to the posterior densities of non-linear functions of the parameters provided enough material for the first half of John’s 1990 thesis (see Leonard, Hsu, and Tsui. Bayesian Marginal Inference, JASA 1989).          For the second half of his thesis, John developed a Bayesian analysis for mixtures, and this was later published in Ann. Inst. Stat. Math. with an interesting application to the estimation of survivor distributions for the Madison colon cancer data where some of the observations are censored. Fluoricil-6 was apparently the most efficient drug, but only because a number a patients dropped out of the trial because of the drug’s severe side effects.          I published a number of papers with John after he’d moved on to the University of California at Santa Barbara, and our 1999 book. These included a joint paper in Statistica  Sinica with Doug Bates’s student Christian Ritter. [Doug, who was one of George Box’s closest buddy’s, was one of the most prolific members of the department e.g. his research on the geometry of non-linear regression and his development of our department’s computer system; he’d worked with Don Watts at Queen’s University.  Don was a former STATLAB director in Madison, and his musical wife Valerie once played for the BBC. I once partied with them at their beautiful farm in Ontario, though the top soil was extremely thin. Christian followed in Doug’s footsteps by using our Laplacian t-approximation to analyse a tricky non-linear regression model in chemistry. Christian is now happily married to his fellow-student Linda Danielson and working with her at the Catholic University of Louvain.] My best paper with John Hsu was undoubtedly Bayesian Inference for a Covariance Matrix, that appeared in the Annals of Statistics (1992). John helped me to finally unravel the complicated math that I’d formulated at MRC in the early 1980’s, by reference to the recursive solution of Volterra equations developed by the mathematical physicist Richard Bellman and numerous tricks with eigenvalues and eigenvectors.          Our multivariate normal prior for a diagonalization of the matrix logarithm of the covariance matrix provided a very general alternative to the inverted Wishart conjugate analysis developed by Gwyn Evans in 1965, and John’s computations of the exact marginal posterior densities of the parameters of interest were ingeniously devised. They yielded a generalisation of my Technometrics (1975) method for the simultaneous estimation of several log-variances, which came out of my 1973 Ph.D. thesis.          Other authors (e.g. the economist Neil Shepherd) have tried using a multivariate normal prior for the logs of the variance components of a general covariance matrix, but it is then virtually impossible to maintain positive definiteness of the matrix. None of the economists seem to have even heard of my Technometrics paper, since they never cite it, but I don’t get worked up about these things any more. They’ve probably never even heard of Technometrics.          An Associate Editor, who I assumed to be Jim Berger, was instrumental in encouraging us to rewrite the first submission in more rigorous terms, and I sometimes wonder (I’ve forgotten why, though I remember some comment about bees) whether the kinder of the referees was Dennis Lindley. The published version, which appeared at the front of the journal (this impressed Arnold Zellner, if nobody else!), was to earn me a $5000 salary rise, and I have Doug Bates to thank for that. During my years at Wisconsin, I taught 709-710, a very advanced mathematical statistics course that prepared students for the totally sadistic Ph.D. qualifier, but we all needed to be primed on the Berkeley-style asymptotics by my teaching assistant Doug Nychka. Doug, who is now the Director of Mathematics in the Geosciences at NCAR in Colorado, was one of the several of Grace Wahba’s ‘Splinemen’ who possessed a keen eye for practical data.          A Splineman called Jim Wendelberger was also born to live in America. He produced the thickest Ph.D. theses (on world climate maps) that I’ve ever had to examine. He married Joanne Roth and I danced with Grace Wahba at their wedding. Joanne later impersonated me during one of the more poignant Christmas skits in George Box’s house, waking up as a talkative arch-Bayesian after nodding off with my shirt hanging out during a seminar about something entirely different.          Jim and Joanne moved on to highly successful careers and their three daughters are also successful statisticians. I regularly played pool with Jim in the Badger Tavern and one of our opponents once broke his pool stick over his knee after scratching on the eight-ball.          Jim is currently Director of Statistical Analysis for Urban Science in New Mexico, and Joanne is a group leader at the Los Alamos National Laboratory. Grace’s Splinemen were, with one or two exceptions, usually very kind to my work. However, a hard-pressed Director of STATLAB, who was really quite a decent fellow, once borrowed my 1982 MRC technical report describing a novel Empirical Bayesian approach for semi-parametric logistic regression models from my office, converted it into splines, tagged on a heart disease data analysis, and published a modest generalisation in a subsequently well-cited paper in JASA! Such is the fate of the creative. Everybody else needs their meal ticket too.  I also taught many sections of the interdisciplinary courses Statistics 201 and 301, and the mathematical statistics sequence 311-312 for undergraduate Industrial Engineers. I got into a fascinating political saga after I described the ‘Rachel Welch’ density (the perfectly-smooth bimodal density of the reciprocal of a standard normal variate) to the I.E. students. One of their more redneck senior professors, called Big Steve, I think, didn’t approve of me taking them to the Badger Tavern for a drink and tried to get at my teaching evaluations, the miserable bastard. Perhaps he was scared of me introducing them to Rachel Welch.          Several of my Statistics 775 students, including Jean Deichtmann and Josep Ginebra-Molins, helped me to modify my alternatives to expected utility theory, which are discussed in Chapter 4 of my book Bayesian Methods. Josep is now a professor at the University Polytechnique of Catalonia in Barcelona.   Josep Ginebra-Molins            The advanced undergraduate course Statistics 431 was extremely enjoyable to teach. I highlighted my version of ‘Goodman’s full rank interaction analysis’, quasi-independence models, and the problems with lurking variables that surround Simpson’s paradox. I encouraged the interdisciplinary students to apply this methodology to data sets from their own areas of interest, and to seek real-life conclusions e.g. by interpreting the patterns of the residual interactions in relation to the background of the data.       The 431 students’ individual projects seemed to create a huge amount of social impact in a wide variety of areas (I for example recall an impressivc analysis of the dancing routines of Wisconsin cranes, and a subjective analysis by a nice young lady of drug abuse rates on the Madison campus that refuted the official figures of about 10% by a ratio of three to one), and the students took my dire warnings about lurking variables to heart, on occasions quite publicly.          Alistair Scott, who was visiting from Auckland, and Jerry Klotz were amused when one of the students advised the press that ‘Professor Leonard says that you should consider all the lurking variables before drawing any conclusions’. Alistair thought that I had lurking variables on the brain, and Jerry asked me what they were.          George Box always thought that Jerry had a beautiful wife. I enjoyed going canoeing with him, and we once almost got stuck without a paddle together of the Yahara River. He was highly regarded in non-parametrics, and the discoverer of the Klotz test for heterogeneity of variances.          I have since published the 431 course material in A Course in Categorical Data  Analysis (Chapman and Hall, 1999, with contributions by Orestis Papasouliotis), but the simply-expressed book was, to my disappointment, said to be too difficult for the students by some of the expert reviewers, and bombed. While I was teaching 431, I helped a Geology graduate student called Dennis Kerr to develop new methodology for analyzing geological layers using suitably normalised quasi-independent contingency tables to estimate the transition matrices in Markov chains. I also developed a neat modified profile likelihood procedure, based upon broken and unbroken plate models, to estimate the bottom of the Mid-Continent Rift, for Jon Nyquist, a geology Ph.D. student, fellow chess player, and Antarctic explorer. The methodology is published in 'Flexural Modelling in the Mid Continent Rift', by Nyquist and Wang, in the Journal of Geophysical Research (1988). Jon is currently a Professor of Geophysics at Temple University.     Jon Nyquist   Dennis Kerr   In 1987, I presented the ideas in Statistics 431 in a American Statistical Association short course on Applied Categorical Data Analysis in the Hilton Hotel in San Francisco, and they were well-received. In 1986, I was the statistical expert for nine nursing homes in their case against the State of Wisconsin that attempted to force the State to re-imburse their actual costs. Our first success was to take an appropriate random sample, that could be split in two, from the Wisconsin population of nursing homes. We then used SPSS to give us a bivariate scatterplot of the reimbursed costs and the actual costs for the nursing homes in the sample. When we observed a strange bloop in the plot, we realised that a regression analysis was both unnecessary and inappropriate. Our scatterplot amply demonstrated that it was only the expensive nursing homes which weren’t adequately reimbursed. When I suggested using a Kolmogorov-Smirnov test, the lawyer replied, “That’s a good idea. Let’s go for a drink.” I was later the statistical expert witness for the defence in a case where the State of Wisconsin alleged that Poly America Inc. were selling underweight polyethylene sheeting. I completed an extensive data analysis, but I don’t remember the outcome.          In another case, Rite Hite Corporation claimed substantial damages against Kelley Co. Inc for loss of profits after a patent infringement. I managed to tip the case in favour of the defence by sending their lawyer into court with a copy of Box, Hunter, and Hunter, where he used the Oldenburg Stork Example to convince the judge that the plaintiff’s correlations were entirely spurious. During a bizarre defamation case against Wisconsin Farm Bureau, a court official appeared at my office door and attempted to subpoena both me and Mendel’s pea-breeding data.          In 1992, I successfully challenged an alleged 99.99994% probability of paternity, based upon DNA evidence, in Phillips, Wisconsin. In the same year, I helped Wisconsin Lotteries to win an age discrimination suit. I was involved in a number of cases involving HLA blood typing and DNA evidence, but I always declined the Chicago murder cases. I was an accredited expert witness in the States of Wisconsin, Minnesota, Iowa and Illinois. I screwed up in a case where I was supposed to be defending the Wisconsin Department of Justice against accusations from several prisoners in solitary confinement that their cells were going red hot and icy cold. The data collected by the Justice Department were so ridiculously spurious that I tried to side with the prisoners pro bono, and the powers-that-be were totally unamused. Between about 1985 and his tragic death in 1994, I substantially benefited from my intellectual friendship with my neighbour James A. Koutsky, a UW professor of chemical engineering and president of the American Ceramics Society, who liked the work on modelling by mixtures that we used to analyse the Madison colon cancer data and wanted to apply it to chemical process data. He thought that ‘the human race will go to the stars’ and that ‘our wisdom is with grandmothers’. While heavily agnostic, he also conjectured that gay and lesbian people were created as extra uncles and aunts at the beginning of time, for the purpose of giving additional support to our traditional families.   James A. Koutsky   My literary colleague Allan and I have since called this ‘Koutsky’s hypothesis’, and we only wish that the gay community would take heed of it. It certainly isn’t open to refutation by the creations accounts in Genesis, where it is claimed that God made humans in his own image, male and female alike. However, the head of the Edinburgh LGBT Centre on Howe Street once gave Allan a very blank look. I think that  numerous self-appointed and unqualified gay activists, including a publicly-agnostic retired Bishop of Edinburgh who still expresses his individualistic views from the pulpit at my church, are too keen to perpetuate the myth that people who regard themselves as gay are inherently different.          While I was in Madison, I informally counselled many actively gay people, and I was for a time a local convenor of Integrity-Dignity, a religious organization that was supportive of them, but which had been thrown off holy ground by Cardinal Josef Ratzinger. As I was also the co-organiser of an AIDS/ HIV Ministry and challenged various leading fundamentalists in group debate, I am therefore well-qualified to talk on gay social issues. However, my apparently liberal church in Edinburgh adheres to the PC line and has never invited me to speak. Indeed, they buried an article by Allan and myself on gay issues, the traditional family structure and Koutsky’s hypothesis that we submitted to them for discussion in 2006, and the rector glowered at me for over a year.   Richard L. Brown, M.D   During the early 1990’s, I helped Dr. Richard L. Brown of the UW Department of Family Medicine to apply for an NIH (National Institute of Health) grant to develop a questionnaire that might help to screen potential drug users, who often give false responses in order to protect themselves from prosecution, by asking them conjoint questions about drug and alcohol (i.e. substance) abuse. The gold standard for defining a patient to be a drug abuser was a potentially inaccurate 853 item questionnaire! Rather than using factor analysis, as previously recommended to Richard, to reduce the number of items, I suggested seeking the advice of groups of experts, drug abusers, and recovering drug abusers. The recovering drug abusers were the most insightful, and they helped us to reduce the number of potential items to about nine. We then asked NIH to fund a couple of large surveys that might help us to develop a simple two-item questionnaire with reasonable sensitivity and specificity, and to confirm that this would be similarly efficient for patients with different characteristics and ethnicities.          When the grant came through, we appointed Orestis Papasouliotis, a broadly-qualified Statistics graduate student from Salonika, to be our research assistant. He helped us to design an efficient conjoint questionnaire where the patient was screened as a possible drug abuser if he answered positively to at least one out of two simple questions,  and we published three papers with him and Laura Rounds in family medicine journals. Rich was awarded tenure on the basis of our results. He is still using a version of our Wisconsin Substance Abuse Questionnaire to screen potential abusers, and thousands of drug-abusing Wisconsinites have benefited from our methodology. Around that time, I collaborated with Kam Wah Tsui on the supervision of two more of his Ph.D. students, Mohamed T. Madi and Tom Y.M Chiu. This led to a paper with Madi on Bayesian estimation for shifted exponential distributions that appeared in the Journal of Planning and Inference (1996). He’s now a Professor and Associate Dean at the University of the United Arab Emirates. [See also item (1) in CDC section.]          And we encouraged Tom Chiu, even though he was dead scared of the maths, to follow up on my 1992 paper with John Hsu, by developing a matrix logarithmic model for several covariance matrices, combined with a linear model for the mean vectors. We used maximum likelihood estimators for the unknown parameters and attempted to prove their asymptotic normality. This proved to be a monumental task, and Tom and I needed to spend our Saturday mornings struggling through exceptionally complex versions of Berkeley-style asymptotics, while Kam prompted us during the week.          Our results were published in our 1996 paper in JASA and I’m proud of the theorems, if not the tentative practical work. Tom Chiu moved on to become a master statistician with SPSS in Chicago, and he has since advanced further. I was invited his traditional Chinese wedding, and this was a wonderful experience. The random effects version of the matrix logarithmic model relates also to the Leonard-Hsu 1992 Bayesian paper in the Annals of Statistics. It has been successfully applied by a number of econometricians, including James Le Sage and Kelley Pace, to multivariate time series and spatial random effects models, and can explain multivariate stochastically volatile data. I was delighted to discover these applications in my retirement during a Google search. The econometricians have given us lots of credit, which is rather refreshing.          Maybe somebody (e.g. another of Kam’s students) would like to use our Volterra integral equation/spectral decomposition technique to derive the Jacobian of the matrix logarithmic transformation. It would be very useful to be able to use the Jacobian when developing importance sampling procedures for random covariance matrix models.       Chong Gu   Michael Hamada   Taskin Atilgan       Mohammed Madi   Linda Danielson, Christian Ritter and their son     During early 1995, I summoned up enough courage to visit Britain for the first time in sixteen years. After a nostalgic stay in London, I met up with Professor Tony  O’Hagan and his wife Anne in Nottingham. They were most hospitable, and Tony told me about the vacant Chair of Statistics at Edinburgh.          I decided to apply for David Finney’s former chair in order to be closer to my daughters in England, and because my nephew and his family were living in Edinburgh; he’d recently graduated from the University’s medical school. I consequently found myself returning to Britain one more time (while I was recovering from some nasty surgery in Wisconsin) and explaining away my U-shaped career to a formidable interviewing committee in the Old College of the University of Edinburgh.          Mike Titterington and Adrian Smith were the external advisors to the committee, but I was remarkably unphased. To their credit, they followed the British tradition of reading several of my publications. These included my 1992 Annals of Statistics paper with John Hsu. I also sent Mike and Adrian a copy of a highly mathematical single-authored article that Rich Johnson had accepted for Statistics and Probability Letters (1996), after giving me substantial help and advice. In this article, I proposed using a multivariate Dirichlet process as a mixing distribution when constructing an exchangeable sampling distribution for uncontrolled data. This related to research that I’d completed at MRC during the early 1980’s, but which I’d failed to extend and apply well enough to get published in JRSSB. During my interview, I tried to sound perceptive and visionary. To my surprise, Vice-Chancellor Sir Stewart Sutherland subsequently offered me Scotland’s premier Chair of Statistics, even though there were at least three highly qualified further applicants, including two incumbents of other Scottish chairs. When I accepted, I took a year’s leave of absence from Wisconsin as insurance. I succeeded in selling my house by Lake Wingra for a handsome profit, just in time for my move. I always land on my feet, according to Rich Johnson at least. Early in August 1995, I visited the Mexican festival in Santa Barbara with John Hsu, before leaving Madison on the bus for O’Hare airport.  By the end of the month, I was watching the human circus on the Meadows, at the Edinburgh Festival, and I haven’t set foot in the United States since. I learnt shortly afterwards from my older daughter that Edinburgh was one of the highest-ranked universities in Britain, and even compared with Oxford. Around the time of my departure from Madison, Gouri Bhattacharyya, who’d appointed me to my position there in 1979, retired unexpectedly early. While I heard some whispers across the lunch table, I can only guess at the political machinations that lead to this decision. Gouri was a brilliant, and charming, gentleman, though he would insist on attending the departmental picnics in Vilas Park in an officious-looking suit.   Tom Leonard - The Life of a Bayesian Boy       CHAPTER 7: THE UNIVERSITY OF EDINBURGH   Tom's former colleague Angelika van der Linde (Oldenburg, 2012)   "The real thing in this world is not so much where we stand, as in what direction we are moving." (Julius Nyerere)   The Department of Mathematics and Statistics of Edinburgh University was housed in the James Clerk Maxwell Building on the King’s Buildings campus. It consisted of the pure mathematicians, including several theoretic, self-protective probabilists, the traditional applied mathematicians, who were led in fine style by David Parker, a successful O.R. group, and several isolated statisticians who taught from lecture material that’d been prepared and meted out at the time of the Ark. The statisticians were the residue of David Finney’s and Peter Fisk’s old Department of Statistics plus the newly-appointed double-bootstrapper Bruce Worton. He’d published some interesting research with David Hinkley, who I’d recently met with a beautiful lassie during a convivial party in John and Serene Hsu’s house in Santa Barbara. Bruce’s position was described to me as the new appointment that came with the chair, but the highly-accomplished applied statistician Crystal Donnelly had, without my knowledge, been encouraged by the manipulative mathematicians to leave for Oxford in order to accommodate this, and her probabilist boyfriend Ben Hambly departed in a huff shortly after she left. They were presumably unaware of the full nature of the ripples from above, and I only heard the complete story later,  from an Associate Dean. I’d inherited a tenuous political situation. The albeit well-meaning departmental chairman had extremely bizarre views on what Statistics really was, and regarded us as a mathematical example. Furthermore, a totally mysterious, apparently papier maché Government quango of ex-civil servants called BIOSS (Biomathematics and Statistics Scotland), who described themselves as a charity, was sticky-taped to our belly from the floor below. Their functions seemed, at first, sight to be to siphon off the grants in Agricultural Statistics and to award each other advanced doctorates in Statistics and honorary professorships without actually producing anything  substantial. However, BIOSS’s director Rob Kempton, who was out of Oxford, proved to be a fine statistician and supportive colleague. He helped me to trace my great great grandfather’s (the Rev. Dr. Francis Bryant of Peter Tavy) records at Wadham College, where my accomplished ancestor was awarded a third class honours degree and a D.D., and to discover that my great great great grandfather was a gentleman in Holborn.   Under Rob’s directorship , BIOSS proved to be immensely influential though rather all-constraining in political terms. Chris Glasbey published a series of influential papers on Bayesian Image Analysis, one of them jointly with Professor Kanti Mardia of Leeds who was one of the most brilliant statisticians in Britain.       Rob Kempton (1946 - 2003)   Ian Main   Alan Izenman   Orestis Papasouliotis and family   I was pleased to be able to make Bruce Worton’s appointment permanent; he was an excellent teacher, particularly on a large service course to the biologists, and I’d been intrigued by the bootstrap ever since I’d listened to Bradley Efron talking about it in Monterey in the early 1980s.  I was also delighted to be able to bring in my erstwhile research assistant Orestis Papasouliotis from Madison as the research associate in our hastily-devised STATLAB. I became its first director, and several other statisticians in the department occasionally collaborated. STATLAB’s immense success was to later on be seriously undervalued by our Faculty Office. In hindsight, I believe that we achieved monumental heights. Bruce Worton and I started off by helping Dean Geoffrey Boulton to analyse his educational foresight data, and he extrapolated our conclusions all over the place. Bruce did some useful research on the frequencies of bird species for RSPB, which also contributed to STATLAB’s success. I got him started with some theoretical suggestions for a Bayesian modeling problem, and he later published some business applications, with George Stretfaris, as well as publishing some applications of other methodology with BIOSS. He and Orestis later co-published their analysis of the Scottish glaucoma data. [see item (8) in my CDC section] Orestis and I completed a major consultancy for Northumbria police by analysing aggregated patient records pertaining to a multiple murder inquiry (a nurse in Newcastle was suspected of routinely overdosing her patients). During our complicated analysis we discovered that Bayes factors, when comparing a one-sided null hypothesis with an oppositely one-sided alternative hypothesis, can work well in frequency terms and that Lindley’s paradox can be avoided. While we came up with a number of significant conclusions, with the help of several jolly police officers visiting from Newcastle including the superintendent himself, the nurse was acquitted, possibly as a result of our analysis. STATLAB also made substantial contributions to the template modelling of the amount of mutton in sheep, and to the Bayesian statistical analysis in Astronomy of data relating to ionising flux in high redshifts. See items (2) and (6) of our CDC section. Orestis proceeded to develop a Bayesian approach to the analysis of covariance, as his Ph.D. topic in Edinburgh, using judicious applications of MCMC, and he applied this to a large forensic science data set contrasting different types of criminals that was provided to us by Tony Busutil, the University’s Professor of Forensic Pathology.          The conclusions are described in some detail by Orestis in item (8) of our CDC section. They suggested that paedophiles could not be detected by neuropsychological tests, given the data then available.  I’d been previously unaware that they were published by Leonard and Papasouliotis (2002) in the Encyclopaedia of Environmetrics, and it was a pleasant surprise to discover that these contributions had been recognized in the literature. Orestis and I also developed a Bayesian backwards prediction procedure that drew inferences about the amounts of drugs smuggled in by criminals during previous trips into the country, given the amounts that’d recently been discovered in their stomachs. I co-authored a long paper in JRSSA with Orestis et al, which described our new methodology.          We later developed a random effects multivariate generalisation, during a congenial visit by Alan Izenman from Temple University, which accommodated measurement error when taking replicated readings of the amounts of drugs.           Unfortunately, we discovered in hindsight that Lothian and Borders police had provided their contact person Colin Aitken with extremely precise measurements whose errors were so small that we were unable to develop a meaningful practical example! But a feather in the cap for the police. And Alan had a great time with us anyway. As a major component of his duties for STATLAB, Orestis analysed numerous data sets from around the university, including one that was left outside his door in a brown bag by a girl with strange views of Statistics.  Highlights included an application of Laplacian approximations to data in Astrophysics that simulated new star systems, and an application of Geoff McLachlan’s package for multivariate mixtures to an analysis of the Lepenski Vir archaeological data, which reported the nitrogen and carbon content of Mesolithic and Neolithic skeletons.           The Lepenski Vir results are briefly described on page 3 of my 1999 book with John Hsu, and we came up with a clustering that wasn’t anticipated by the  traditionally-minded archaeologists who always expected the data to divide neatly into two groups. We later developed a modified Bayesian solution to the Fieller-Creasy problem that enabled Orestis to show, by analysing an exhaustive stream of datasets, that pronounced cytoplasmic pH gradients are not required in plant and fungal cells. We reported these results, with Parton, Read et al, in the Journal of Cell Science (1997). Orestis extended his long list of publications when he moved to Serono International, a pharmaceuticals company in Geneva in 2001. He now has a senior appointment with them, and hopes to return to Edinburgh soon with his daughter to visit the zoo. John Hsu visited us from UCSB on several occasions, and was appointed to an honorary fellowship in our department. In 1996, John, Li Sun, Irwin Guttman, John and I published a paper in JASA that used Laplacian approximations to marginal posterior densities for parameters of interest in normal random effects models, and also refuted the 1972 Lindley-Smith estimates (Irwin was fascinated by this, though I was bored to tears about the damned things by know). An earlier version had been well-received, with a great deal of laughter, when I presented it at the founding 1993 San Francisco meeting of ISBA.          During 1997, two of the co-authors of the 1996 JASA paper were nevertheless irrationally attacked from a source that I’ve been asked to say was unknown, but it wasn’t Dennis Lindley and one of us suffered the consequences. While I was gratuitously insulted in the most personal terms, which seemed to make an assumption about my orientation, it’s difficult to prove cause and effect. I’d hoped that the Leonard-Lindley-Smith saga had been put to bed, but it would rear its head again briefly in 1998 at Valencia 6 before the alcohol and John Deely took over. I’d been delighted to be able to appoint Angelika van der Linde from Bremen to a lectureship in the department on the recommendation of Bernie Silverman, and this was supposed to be a research appointment.  She’d published some seminal theoretical  results on Gaussian prior processes for regression models, and she proceeded to develop DIC with David Spiegelhalter, and powerful methods using reference priors with Jose Bernardo, who visited us later. She was later of great service to ISBA, and in particular worked as production editor for the Society’s international journal. She was also a wonderful lunch-time companion.          Angelika was dumbstruck when the mathematicians asked her to expend a large amount of her work effort preparing model homework and exam answers, rather than spending her evenings attending the film festivals.  The undergraduates would typically wait for the model answers without doing their homework, and then complain if an exam question didn’t relate to a previously circulated solution. Many of them didn’t take lecture notes either! [In their final year, many of the students’ scores were ratcheted up by the department’s Scrutiny Committee. This ensured that most third-class students received upper seconds and their meal tickets. We were always under strong pressure from the financially-orientated Faculty Office not to fail any students whatsoever] In 1998, Angelika and I travelled to the Sixth Bayesian Valencia Conference together, a nostalgic return for me after nineteen years, and it was good to see Peter Freeman again. The conference was held in the Hotel Las Fuentes on the Spanish Mediterranean coast, just like the first one, though the seafood wasn’t quite as appetizing, and I enjoyed the cold water springs on the beach, where I played football with Richard Smith from North Carolina and chatted about the fundamentalist Bayesians at Warwick with Peter Lee, the colourful Provost of Wentworth College from York, while Adrian Smith, still looking remarkably young, was kissing the ladies.          Dennis Lindley was at his charming best. In 2002, he would receive the Royal Statistical Society Guy Medal in Gold from Peter Green for his pioneering developments in Bayesian Statistics, fully twenty-six years after his retirement. My overriding concern during the poster sessions was that far too many doctoral students were using MCMC when analysing models that would have benefited from a more direct prior-to-posterior analysis; they were therefore wasting their talents. However, Gelfand and Smith were very much revered in this respect, and I came across as an old codger with eccentric opinions. Steve Fienberg teased me with remorseless good humour during his after-dinner speech, and brought the house down with a series of jokes regarding my 1975 paper in Technometrics. Jim Zidek thought that I came out of it well.          Later that evening, I played the Rev. Thomas Bayes returning from Heaven in a skit prepared by Tony O’Hagan, the Master of Ceremonies of an otherwise musical cabaret. My adventures with the wandering microphone brought the house down once again. The script has been published on the Internet by Brad Carlin, and a picture of me being interviewed by Tony can be tracked down by sourcing Pictorial Tribute: Bayesian 6 Cabaret. Life is a cabaret, my friends, life is a cabaret! After all that, John Hsu and I finally completed our book Bayesian Methods: An Analysis for Statisticians for Interdisciplinary Research Workers (1999), the fourth advanced graduate text in the Cambridge Series in Statistical and Probabilistic Mathematics, published by Cambridge University Press.          The book was well received by the critics, with some quibbling about its level of difficulty and its focus on the whole gamut of Bayesian marginalization procedures, including MCMC. The book has sold well (about 5000 copies), with a special edition in China, and it’s still being used by Kam Tsui at the University of Wisconsin as part of the course materials for Statistics 775. Moreover, Professor Charles Franklin used it for several years as the core text for his UW graduate course for political scientists. Michael J. Evans of the University of Toronto wrote in Mathematical Reviews that ‘This book provides excellent up-to-date coverage of modern Bayesian statistics. The book is clearly written and at a reasonably high level. Outstanding features of the text include a number of significant applications of the methodology, the use and comparison of the AIC and BIC model selection criteria in several contexts, a somewhat unique treatment of the axiomatization of Bayesian decision theory through utility, discussion of the frequency properties of the procedures, and interesting and relevant self-study exercises that extend and deepen the content of the book.’   Michael Evans   STATLAB continued to be very successful. Orestis received BP funding from Professor Ian Main in Geophysics to work on the statistics of earthquakes and oilwells, and the three of us published three papers together in international geophysics journals. One of these was authored jointly with Kes Heffer from BP, while he was moving to Heriot-Watt, and another with two further geophysicists. We were particularly concerned about long term (i.e. long distance) correlation between earthquakes, and between oilwells.          Our best achievement was the development of a simple algorithm for discerning the couplings of injector wells and producer wells in a large complex oilfield that might give rise to the best output. The fifth chapter of Orestis’s thesis is devoted to this topic, and contains a fascinating map of a large North Sea oilfield. His external examiner, David Wright of the University of Plymouth, said that he was most impressed most of all by this practical contribution. [I also knew Julian Stander and I’d served as external examiner for one of their students at Plymouth, as well as visiting them to give a seminar] The University of Edinburgh have since obtained international patents for our method. My older grandson was pleased to hear that I’m an inventor.   Julian Stander   Around that time, I was a co-author of three joint papers on radial basis networks in the Artificial Intelligence literature with the international chess master Mark Orr [with whom I’d won the Edinburgh team championship in 1996 with the Wandering Dragons. In 1992, I was chess champion of North-East Wisconsin]. However, as I remember, my only substantive contribution was to Mark’s EPSRC grant proposal, since one of my boy scouts (called Jet, Jip, or whatever) preferred to go walk-about. But here’s a big thank you to Mark. Irwin Guttman visited Edinburgh from SUNY at Buffalo for several months during 1998, and he still remembered my 1975 University of London seminar on Bayesian contingency table analysis. We developed solutions to a couple of research problems together, and he and Orestis helped me to complete my book A Course in Categorical Data Analysis that I was writing under unfair time pressure from the incoming administration at Chapman and Hall. They both thought that the end product was rather good. In 1999, Mr. John C. Duffy returned to the Statistics group, from the Scottish Health Department, after a long absence. He’d previously published some very interesting research with Timo Alanko of the University of Helsinki on the estimation of the distribution of alcohol consumption. I’d reviewed Alanko’s Ph.D. thesis on the same topic, and this helped him to publish his thesis as a book. John is currently (as of March 2012) Deputy Director of Knowledge Management for the Scottish Higher Education Funding Council, and we’ve discussed a variety of statistical ideas and all the intrigue together over the years.          In 1999, I took the opportunity to work with John on a meta-analysis problem relating to several 2x2 contingency tables and the Mantel-Haensel model, and we developed novel Laplacian approximations to the posterior densities of the common measure of association and other parameters of interest, under fixed effects assumptions. Our methodology is published in Statistics in Medicine (2002).          In our first practical application we combined six different studies of children with acute otitis media (an ear condition), where each study compared the proportion of patients experiencing pain 2-7 days after receiving an antibiotic treatment with the proportion in a control group who experiencing pain after 2-7 days. While the approximate posterior density of the common log measure of association was skew to the right, it showed in precise terms that pain and the antibiotic treatment were strongly negatively associated. This conclusion was further validated by a graphical variant of a L’Abbé plot. In our second practical application we investigated three different studies of children developing contralateral otitis media in a treatment group. and a control group. After investigating a variety of posterior densities, we concluded that the common measure of association assumption was not completely reasonable. In such cases, the Mantel-Haensel test should be employed with extreme caution.     John and Serene Hsu, Santa Barbara, California (Christmas 2012)   Tom Leonard - The Life of a Bayesian Boy       ARMAGEDDON     By the year 2000, my U-shaped academic career was all-in-all highly successful and achieving a new peak. But during that summer, I flew off the handle of the U (while I was trying to develop rational alternatives to Bayes factors!) by experiencing a ginormous breakdown, leading to a year of severe ill health and my early retirement in the Fall of 2001 at age 53.          John Hsu visited me from Santa Barbara during this traumatic period and pulled me out of a deep depression. I also received lots of moral support from Angelika van der Linde, Orestis Papasouliotis, John Duffy and Ian Main. I will always be grateful to them, though I was surprised that my medical confidentiality was not correctly observed by my departmental chairman, or the Dean.          My breakdown was caused by mind-boggling physical health problems, cruelly severe political pressure down the line of command on the less productive members of the Statistics group from the eagle-eyed Dean of Science and Engineering who’d succeeded the affable geologist Geoffrey Boulton. The pressure was catalysed by my ruthlessly compliant departmental chairman, and a death threat and some crazy experiences when I was foolish enough to try to expose a gang of criminals to Fettes police. Such is the human condition. I’m glad that I retained my sense of humour.          My life after retirement is satirised in my still-to-be-completed novel In the Shadows of Calton Hill. Professor Simon Southwood is a slightly wackier version of myself.     Tom Leonard - The Life of a Bayesian Boy       THE DEAN, JIM CROW, AND THE FORENSIC SCIENTISTS     In 2000, the incumbent Dean of Science and Engineering was a world leading geneticist who’d enjoyed visiting the great Jim Crow in Wisconsin. Jim and I had both published contributions to the discussion of ‘Parenting Probability, an Unnecessary Artifact’ by my colleague John Wood in the Journal of the American Mathematical Association (1991), where we expressed diametrically opposing opinions about paternity testing based upon HLA blood typing and DNA evidence.   Jim Crow            Some of my objections are summarised in ‘On Bayes Theorem, Paternity Testing, and Wisconsin Law’, Department of Statistics, University of Wisconsin-Madison Technical Report (1985). I continued the debate, with mixed receptions, when I arrived in Scotland e.g. at the 1996 RSS Edinburgh Conference on Forensic Statistics, during my poorly-presented talk at a joint meeting of the RSS in London, and in a written contribution to the discussion of a paper read to the RSS by Ian Evett, Adrian Smith et al.         Bruce Weir of the University of North Carolina said that he was sure that everybody in the U.S. was glad that Professor Leonard had returned to Britain. That was after my 1996 conference presentation to the RSS in Edinburgh, when I referred to a paternity testing case in Decorah, Iowa.   Bruce Weir   My client in Iowa had been assigned an alleged 99.99% probability of paternity even though the other, equally rich, named candidate was nowhere to be found. Confident of victory, Rosie testified on the stand that she’d been laid by ten construction workers during the month of conception. When I took the stand, I demolished the scientific basis of the alleged probability of paternity e.g. by referring to more appropriate prior probabilities, and my client won his case out of hand. My revelations about Rosie seemed to set the RSS conference alight. Indeed, Ian Evett verbally attacked me during his formal speech at the otherwise convivial conference dinner in Pollock Halls, while Phil Dawid was making jokes about construction workers to the beautiful Bayesian lady (Julia Mortera) sitting at my table. I decided against asking the security guard to throw Dr. Evett out.   Ian Evett   Maybe I was seen as a threat to mathematical genetics as a whole. In 1995, and three years before the Dean was elevated to his position, he’d reportedly objected to my appointment to Edinburgh upon his return from a trip to Wisconsin. John Duffy knows a bit more about this.   See also:   (1) Bayes Theorem in Criminal Cases on pp 77-78 of Bayesian Methods by Leonard and Hsu (1999) (2) Item 13 (The DNA Evidence Controversy) of Contributions, Discussion and Corrections section (click on button below) Tom Leonard - The Life of a Bayesian Boy       MY EPITAPH   It is not only the leaders who lead. Some of us lead from the back.   Plymouth Sound from the Hoe   While I was not obviously as successful as my more eminent contemporaries, I believe that my shortcomings were counterbalanced by my rich, though at times bittersweet, experiences of real life and my interactions with a wide range of people, many of whom I tried to encourage in respect to their self-integrity. And because I can boast a dynasty of highly perceptive descendents. And not everybody can claim that.          My experiences included my chess games against grandmasters, my vibrant social life, my religious experiences as a non-judgemental Trinitarian, and my December 1989 speech in Madison, Wisconsin, against gay discrimination in the military that appears, in hindsight [it is useful to search Google on this] to have created substantial, and at times quite frightening, impact across many other campuses, that ultimately benefited our gay, lesbian and transgender communities. [See Appendix] This is not to forget my struggles with district attorneys, genocrats and forensicrats, when I was questioning their thoroughly misleading purported probabilities of paternity and probabilities of guilt in civil and criminal cases involving HLA blood-typing or DNA evidence. Indeed, many U.S. district attorneys settled cases when they heard that I was coming, and several defence lawyers mentioned the name Tom Leonard without even contacting me.          This scenario may well have brought the international genetics profession down on me in the years preceding my early retirement, though I certainly wouldn’t be able to prove this. Bruce Weir, the leading prosecution expert from North Carolina, didn’t like me, and neither did the unscientific elements of the British Forensic Science Service. In my worst moments, I wonder who really finally got me. While I have usually spoken truth without guile, I have never wittingly run roughshod, or pulled tricks on, any of my colleagues, or glossed over any deficiencies in my research. I pour scorn on those who do so, or create false images, in order to enhance their careers or glorify their international reputations. These people know  who they are, and they will answer to their gods.          While my family, health and career seem to have been damaged over a period of time by a trio of manipulative British-based Bayesians and not exactly helped by a redneck non-Bayesian departmental chairman during the early 1980s, they’re of course all forgiven in Christ Jesus. [Professor Shuggy Montmorency's suspicious death by drowning in a seedy jacuzzi (See Ch.14 of my Calton Hill novel) is of course a fanciful construction!] Thank goodness we had George Box to entertain us.     I completely recovered my cognition in October 2011, after refusing to continue taking my health-damaging mood stabilizers, and I am now thinking sharper and more politically than ever before. Since then I have also been far more productive than ever, as evidenced by the mass of totally sane material on this website.   In December 2012, I was elected Fellow of the International Society for Bayesian Analysis, which I devised with Arnold Zellner in 1992. During the first few months of 2013, I joined in the discussion during three entertaining meetings of the Edinburgh Section of the Royal Statistical Society, on medical and legal issues (The speakers were Professors Susan McVie and Sheila Bird, and Dr. David Lagnado of the Universities of Edinburgh and Cambridge, and University College London). I met up with Colin Aitken, now Professor of Forensic Statistics at the University of Edinburgh and whose career I’d previously nurtured, for the first time in thirteen years, and I also befriended Dr. Alan Forest, the Head of Credit Scoring at the Royal Bank of Scotland, and met Cecilia McIntyre, the Scottish Housing Statistics doyenne, one more time.   In June 2013, my former student, research associate, and prolific co-author, Orestis Papasoulitis, visited Edinburgh and we went for supper together in Ciao Roma. This was the first time we’d seen each other since September 2000, when we enjoyed a meal in the same restaurant with Angelika van der Linde and her partner.   As of late June 2013, I am focusing on poetry, playing about my 750th game on Chess.Com with an adjustable rating which reached 1752 before dipping lower again, and being actively involved at St. Paul’s Scottish Episcopal Church below the Royal Mile. I am currently funding the Edinburgh Equal Collective Advocacy Forum (EECAF), a charity for the mentally disadvantaged, out of my Auntie Nancy’s legacy, and I am heavily involved, with the help of my friends Thomas and James, in organising the ‘Double Lambda Study’. This concerns a statistical survey of mental health outpatients in Midlothian regarding the observed benefits and disadvantages of their psychiatric medications. I have already collated a huge amount of prior knowledge, largely by networking across several subpopulations, including our LGBT community, and I am taking it upon myself to confront the Scottish Government and other authorities on related issues.   My novels ‘In the Shadows of Calton Hill’ and ‘Grand Schemes on Qinsatorix’ contain elements of academic satire. (Professor Dirk Charleston is a totally fictional representation of the worst possible University Distinguished Professor!) They are published, appropriately colorized and sectionized on my literary home page.        Following the sad death of my Ph.D. supervisor Dennis Lindley during December 2013 at age 90, I quite unexpectedly achieved international recognition one more time, at age 66 and following over twelve years of retirement, with the publication by John Wiley &Son, and by the Royal Statistical Society (in Statslife), of my invited articles entitled A Personal History of Bayesian Statistics. The first of these celebrated the 250th anniversary of the publication of the Bayes-Price paper. I was to receive two further honours from Wiley (hot article of the week and a featured interview). I am extremely grateful to the Wiley editors David Scott and Alison Oliver for their outstanding support in the face of lots of flack from some quite hostile members of the Bayesian Establishment. Please look at the top of my home page for further details. If you click on REVERB DENNIS LINDLEY and ‘Thomas Hoskyns Leonard Bayesian’, then this will give you some idea of the international impact of my Bayesian history, I wrote 180 pages in three months, after the American Editors of Wiley read this Life of a Bayesian Boy on my website. Jeff Harrison, my flamboyant former Chairman at the University of Warwick passed away in the Lake District at age about 76 during the preparation of my article, after forsaking academia some 13 years previously. But the Bayesian world is now grieving the tragic death of Professor Susie Bayarri of the University of Valencia, at age 58. Such a brilliant visionary and wonderful person, head and shoulders as a human being above many of the rest. I first met her at Valencia 1 in 1979, when she was a vulnerable young student, but Morry de Groot took her under his wing. As of September 2014, I have rejoined the statistical establishment by becoming a, very active, Committee member of the prestigious Edinburgh section of the Royal Statistical Society, and I have presented a talk to them in the International Centre for Mathematic Sciences (ICMS) on The Early History of Bayesian Statistics, with lots of colourful slides prepared by my friend Thomas Tallis. My fellow committee members have given me lots of friendship and support. I recently attended a high level meeting on the future of Forensic Statistics, organised by Professor Burkhard Shafer of the Edinburgh Law School in the Old College of the University of Edinburgh. I added my support to Professor Shafer’s objective of replacing the misleading Bayes factor and likelihood ratio formalisms and idiosyncrasies (which are much too dependent on prior and genetic assumption) by so-called Big Data analysis. I finally decided against attending the ‘coherent Bayesian’ reunion at UCL on 19th September 2014 where they celebrated the Lindley years (1967-1977), and I was very sad at missing out on the chance of meeting up with some of my former fellow students. Sir Adrian Smith, the now highly controversial Vice-Chancellor of the University of London, doubtlessly ruled the roost. I wrote a quite satirical poem entitled ‘UCL Reunion’ (I sent a copy to Barry Leventhal) and I’m still wondering whether to publish it on my Leith Walk Rhymers Youtube page. Please google this page to see a video of me reciting my poem ‘Wherefore Dennis?” I’m almost getting a bit Machiavellian myself as old age approaches. Maybe I should join the club! In January 2015, I was re-diagnosed, at age 66,as suffering from life-long ADD, attention deficiency disorder, a neurological condition which enhances the subconscious thought processes. I may not therefore be as crazy as previously envisioned!                                           If you are what you should be, you will set the whole world on fire (Catherine of Siena)     Tom Leonard - The Life of a Bayesian Boy       The Field House, UW Madison   APPENDIX   A primary-source document relating to a full meeting of the faculty of the University of Wisconsin-Madison in the UW Field House on 4th December 1989, which received national attention.   ‘They’re in for it now!’ as John Nohel, the Director of the Army’s Math Research Center, said, following my speech, to Professor James Koutsky of the UW Department of Chemical Engineering, and our faculty responded by, quite  unexpectedly, voting against the military, by about 350 votes to 250.  Several of their  officers were sitting in full regalia in the front row. Professor David Runyon from UW Whitewater took a film for his television channel and lodged it in the State Archives, and several people ran up to me in the street to thank me for my contribution, which was generally acknowledged as completely turning the tables on the military at the end of an otherwise insipid and quite unconvincing debate.            During my surprisingly devastating speech, I reported that a U.S. army captain had advised me, at an otherwise convivial Second Thursday reception, that ‘these freaks have never even opened a bible’. I also discussed a high-flying naval student in Annapolis who’d been stripped of his degree simply because he expressed his fears to his chaplain that he might be gay. I more generally objected to the intrusions perpetrated by the US military on the innermost thoughts of American students.          Assistant Attorney General for Winconsin, Daniel O’Brien congratulated me afterwards, and he’s visited me in Edinburgh since. The leaders of Madison’s gay community, who were none too keen to raise their own heads above the parapet, congratulated themselves, and gave each other prestigious awards. So much for philanthropy. Please also google "Gay Discrimination in the Military, University of Wisconsin-Madison" The item "ROTC under fire" by David M. Halperin describes the enormous impact of the faculty vote. The reports by Professor Joe Elder of the UW Department of Sociology are incomplete in several respects.            POSTSCRIPT TO LIFE STORY            I conclude my life story on 6th April 2021, largely physically incapacitated by my chest problems, but more mentally alert than ever. I finally returned to the University of Warwick in August 2017, after 38 years to attend a Quakers Annual Meeting. But late in 2017, I suffered two serious falls which damaged my left leg. I nevertheless celebrated my 70 th birthday in Vittoria Restaurant on 24th March 2018, with 37 guests including John and Serene Hsu from Santa Barbara, and Diego and Diane Perez from Manchester.          In July 2019, I returned from UCL after almost 50 years to give evidence with my flatmate Scott Forster, as expert witnesses to the Commission of Inquiry into the History of Eugenics at UCL. It was good to meet Professor Tom Fearn once again, and our verbal and written submissions were well received. I was delighted to learn during January 2021 about the sweeping decisions made by UCL based on the Commission's recommendations,          I'm still living in my flat in Broughton, Central Edinburgh after over 22 years, and trying to survive the pandemic. I stopped attending the Quakers during November 2019, some of them sided with TERFs. rather than trans people, and I now attend my all-accepting parish church, Broughton St. Mary's, e.g. by Zoom