Thomas Hoskyns Leonard


Retired Professor of Statistics, Universities of Wisconsin-Madison and Edinburgh




Readers please note: Most of my bibliography, including a number of important historical references, is encapsulated in the text and should be readily googlable from the information given there. Many of the remaining references are equally important, and a few of my own are included for good measure.


Chapter 2


1. W.O. Jeffreys and J.O. Berger (1991) Sharpening Occam’s razor on a Bayesian Strop. Bulletin of the Astronomical Society 23(3), 1259-1271

2. I.J. Good (1967) Explicativity: A mathematical theory of explanation with statistical application. Proceedings of the Royal Society A. 354, 330-330.

3. I.J. Good (1968) Corroboration, explanation, evolving probability, simplicity, and a sharpened razor. British J. of Philosophy of Science 19, 123-143

4. S.M. Stigler (2006) Isaac Newton as a Probabilist. Statistical Science 21, 400-403.

5. Daniel Bernoulli (1954) Exposition of a New Theory on the Measurement of Risk. Econometrica 22(1), 23-26

Also published as Specimen Theriae Novae de Mensura Sortis in St. Petersburg, 1738

6. S.M.Stigler (1983) Who discovered Bayes theorem? The American Statistician, 290-296

7. S.E. Fienberg (2006) When did Bayesian inference become “Bayesian”? Bayesian Analysis 1, 1-40.

8. S.M. Stigler (1978) Francis Ysidro Edgeworth, Statistician. JRSSA 141, 287-322.

9. D.H.Kaye (2007) Revisiting Dreyfus: A More Complete Account of Trial by Mathematics. Minnesota Law Review 91 (3), 825-835

10. J. Aldrich (2008) R.A. Fisher on Bayes and Bayes’ Theorem Bayesian Analysis 3, 161-170

11. G.A. Barnard (1987) R.A. Fisher-A True Bayesian? International Statistical Review 98 183-189

12. I.J.Good (1965) The Estimation of Probabilities. MIT Press, Boston

13. I.J.Good (1967) A Bayesian significance test for multinomial distributions (with discussion). JRSSB, 29 399-431

14. K.J.Arrow, D. Blackwell, and M.A. Girshick (1949) Bayes and minimax solutions of sequential decision problems. Econometrica 17,213-244

15. T.Leonard and J.S.J. Hsu (1999) Bayesian Methods: An Analysis for Statisticians and Interdisciplinary Researchers. Cambridge University Press, New York.

16. T. Leonard (1980) The roles of inductive modeling and coherence in Bayesian statistics (with discussion) In J.M. Bernardo, M.H.DeGroot, D.V. Lindley, and A.F.M. Smith (eds) Bayesian Statistics 1, pp537-55. University Press, Valencia.

17. Peter Lee (1997) Bayesian Statistics: An Introduction, Second edition. Arnold, London.18. P.Whittle (1958) On the smoothing of probability density functions. JRSSB 20,334-343

19. P.Whittle (1957) Curve and periodogram smoothing JRSSB 19, 38-63

20. A.Birnbaum (1962) On the foundations of statistical inference (with discussion) JASA 57, 269-326

21. T.Leonard (2012) The Life of a Bayesian Boy, www.thomashoskynsleonard.co.uk  (Click Here to view it)


Chapter 3


22. R.E. Kalman (1960) A new approach to linear filtering and prediction problems. Trans ASME D 82, 35-45

23. R.E. Kalman and R.S. Bucy (1961) A new approach to linear filtering and prediction problems. Trans ASME D 83, 95-108

24. F.J. Anscombe (1961) Bayesian Statistics. The American Statistician 15, 21-24

25. D. Ellsberg (1961) Risk, ambiguity, and the Savage axioms. Quarterly J.Econ 75, 643-99

26. D.V. Lindley (1962). Discussion of paper by Stein. JRSSB 24, 285-7

27. B. Efron and C. Morris (1973) Combining possibly related estimation problems (with discussion) JRSSB 35, 379-421

28. F. Mosteller and D.L. Wallace (1963) Inference in an Authorship Problem JASA 58, 275-301

29. R.B. Bush and F. Mosteller (1955) Stochastic Models for Learning John Wiley&Son, Chichester, New York.

30. E.T. Jaynes (1957) Information Theory and Statistical Mechanics. Physical Review 108(2), 171-190

31. E.T. Jaynes (1968) Prior Probabilities. IEEE Transactions on Systems Sciences and Cybernetics 4(3), 227-241

32. R.N.Silver, H.F. Martz, and T. Wallstrom (1993) Quantum statistical inference for density estimation. ASA Proceedings of the Section of Bayesian Statistical Science, pp 131-9

33. D.V. Lindley (1964) The Bayesian analysis of contingency tables. Ann. Math. Statist 35, 1622-43

34. A.W.F. Edwards (1963) The Measure of Association in a 2x2 Contingency Table. JRSSA 26,109-114

35. A. Agresti and D.B. Hitchcock (2005) Bayesian Inference for Categorical Data Analysis. Statistical Methods and Applications 14, 297-330.

36. Biography of Morris H. De Groot (1991). Statistical Science 6, 3-14.

37. I.G. Evans (1965) Bayesian estimation of parameters of a multivariate normal distribution. JRSSB 27,279-83

38. R.A. Johnson (1967) An asymptotic expansion for posterior distributions. Ann. Math. Statist 38, 1899-906

39. R.A. Johnson (1970) Asymptotic expansions associated with posterior distributions. Ann. Math. Statist 41,851-64

40. A.M.Walker (1969) On the asymptotic behaviour of posterior distributions. JRSSB 31, 80-88

41. R.A. Johnson and J.N. Ladalla (1979) The large sample behaviour of posterior distributions which sample from multiparameter exponential families, and allied results. Sankyā, Ser B 41,196-215

42. G.E.P. Box and G.C. Tiao (1968) Bayesian Estimation of Means for the Random Effects Model. JASA 63, 174-181

43. T. Leonard and J.K. Ord (1976) An investigation of the F test procedure as an estimation short-cut. JRSSB 38, 95-8.

44. D.V. Lindley (1971) The estimation of many parameters. In Foundations of Statistical Inference (V.P.Godambe and D.A.Sprott, eds), pp435-455. Toronto: Holt, Rinehart and Winston.

45. L.Sun, J.S.J.Hsu, I. Guttman, and T.Leonard (1996) Bayesian methods for variance component models. JASA 91,743-52

46. G.E.P. Box and G.C. Tiao (1962). A further look at robustness using Bayes’s theorem. Biometrika 49, 419-452.

47. A.Birnbaum (1969) Statistical theory for mental test scores with a prior distribution of ability. J.Math.Psych 6,258-76

48. J.Albert (1992) Bayesian Estimation of Normal Ogive Item Response Curves using Gibbs Sampling. Journal of Educational and Behavioural Statistics 17, 251-269


Chapter 4


49. M. Stone (1974) Cross-validatory choice and assessment of predictions (with discussion) JRSSB 36,111-47

50. J.J.Shiau, G. Wahba, and D.R. Johnson (1987) Partial spline models for the inclusion of tropopause and frontal boundary information in otherwise smooth two- and three-dimensional objective analysis. Journal of Atmospheric and Oceanic Technology 3, 714-24

51. T. Leonard (1982) An Empirical Bayesian Approach to the Smooth Estimation of Unknown Functions. MRC Technical Report, Mathematics Research Center, University of Wisconsin-Madison. Accession Number ADA 114573. DIC Online, Information for the Defence Community

This was one of six MRC technical reports published by Tom Leonard in 1982.

52. S.Geisser (1971) The inferential use of predictive distributions. In Foundations of Statistical Inference (V.P.Godambe and D.Sprott eds), pp456-469. Toronto: Holt, Rinehart, and Winston

53. H.Akaike (1974) A new look at the statistical model identification. IEEE Transactions on Automatic Control 19(6), 716-723

54. H.Akaike (1978) A Bayesian analysis of the minimum AIC procedure. Ann. Inst. Stat. Math 30 (A), 9-14 

55. G.Schwarz (1978) Estimating the dimension of a model. Annals of Statistics 6, 461-4

56. D.J.Spiegelhalter, N.G.Best, B.P. Carlin, and A. van der Linde (2002) Bayesian measures of model complexity and fit (with discussion) JRSSB 64,583-639.

57. D.V.Lindley and A.F.M. Smith (1972) Bayes estimates for the linear model (with discussion) JRSSB 34, 1-41

58. W.G.Fortney and R.B. Miller (1987) Bayesian analysis in random coefficient m-group regression Statistics and Probability Letters 5(2), 135-142

59. N.R. Draper and R.C. Van Nostrand (1979) Ridge regression and James-Stein estimation: Review and comments. Technometrics 21, 431-66.

60. A.P.Dawid, M.Stone, and J.V.Zidek (1973) Marginalization paradoxes in Bayesian and structural inferences (with discussion). JRSSB 35, 189-233

61. E.T. Jaynes (1980) Reply to Dawid, Stone, and Zidek. In A. Zellner, ed. Bayesian Analysis in Econometrics and Statistics, pp 83-87. North-Holland, Amsterdam.

62. T. Wallstrom (2003) The marginalization paradox does not imply inconsistency for improper priors. On-line version arxiv/abs/math/01310006. Cornell University Library.

63. M. West (1984) Outlier model and prior distributions in Bayesian linear regression. JRSSB 46,431-439

64. T. Leonard (1978) Density estimation, stochastic processes, and prior information (with discussion) JRSSB 40, 113-146

65. C. Gu (1993) Smoothing spline density estimation: a dimensionless automatic algorithm JASA 88, 495-504

66. D.D. Cox and F. 0’Sullivan (1990) Asymptotic analysis of penalized likelihood and related estimators Annals of Statistics 18, 1676-


Chapter 5


67. G.E.P. Box (1980) Sampling and Bayes Inference in scientific modeling and robustness (with discussion). JRSSA 143,383-430

68 D.V.Lindley (1983) Comment on the paper by Carl Morris. JASA 78, 61-253. E. Lehmann (1991) Theory of Point Estimation. Wadsworth, Belmont, California

69. J.E. Nyquist and H.F.Wang (1988) Flexural modeling of the Midcontinental Rift. Geophysics Research 93, 8852-68

70. A.J. Cooke, B. Espey and D. Carswell. Evolution of ionising flux in high redshifts. MNRAS 298,708-27              

71. S. Martino and H.Rue (2008) Implementing approximate Bayesian Inference for latent Gaussian Models using integrated nested Laplacian approximations; a manual for the inla-program. Technical Report 2. Department of Mathematical Sciences, NUST, Trondheim


Chapter 6


76. N.Metropolis, A.W. Rosenbluth, M.N. Rosenbluth, A.H.Teller and E.Teller (1953) Equations of state calculations by fast computing machines. J.Chemical Physics 21, 1087-91

77. W.K. Hastings (1970) Monte Carlo Methods Using Markov Chains and their Applications Biometrika 51, 97-109

78. R.Meyer and R.B. Millar (1999) BUGS in stock assessment. Can.J.Fish.Aquat.Soc 56, 1078-1087

79. E.Essen-Möller. Die Beweiskraft der Ähnlichkeit in Vatershaftsnachweiss; theoretische Gründlagen. Mitt. Anthr. Ges. (Wien) 68,9-53


Chapter 7


80. D.Mayo (2010) An Error in the Argument from Conditionality and Sufficiency to the Likelihood Principle. In Error and Inference: Recent Exchanges in Experimental Reasoning, Reliability and the Objectivity and Rationality of Science (D.Mayo and A. Spanos, eds) p305-14. Cambridge: Cambridge University Press.

81. M.Evans (2013) What does the proof of Birnbaum’s theorem prove? Electronic Journal of Statistics 7, 2645-2655

82. W.Hunter Watson (2013) PE01494 Mental Health Legislation. Published on-line at
  © Thomas Hoskyns Leonard, 2014