**I** just received the very sad news that Don Fraser, emeritus professor of statistics at the University of Toronto, passed away this Monday, 21 December 2020. He was a giant of the field, with a unique ability for abstract modelling and he certainly pushed fiducial statistics much further than Fisher ever did. He also developed a theory of structural inference that came close to objective Bayesian statistics, although he remained quite critical of the Bayesian approach (always in a most gentle manner, as he was a very nice man!). And most significantly contributed to high order asymptotics, to the critical analysis of ancilarity and sufficiency principles, and more beyond. (Statistical Science published a conversation with Don, in 2004, providing more personal views on his career till then.) I met with Don and Nancy rather regularly over the years, as they often attended and talked at (objective) Bayesian meetings, from the 1999 edition in Granada, to the last one in Warwick in 2019. I also remember a most enjoyable barbecue together, along with Ivar Ekeland and his family, during JSM 2018, on Jericho Park Beach, with a magnificent sunset over the Burrard Inlet. Farewell, Don!

## Archive for Don Fraser

## Don Fraser (1925-2020)

Posted in Books, Statistics, University life with tags asymptotics, Canada, David Cox, Don Fraser, fiducial inference, fiducial statistics, John Nelder, Nancy Reid, O'Bayes 2019, obituary, Ontario, R.A. Fisher, Statistical Science, University of Toronto, University of Warwick, University of Waterloo on December 24, 2020 by xi'an## complex Cauchys

Posted in Books, pictures, Statistics, Travel, University life with tags Augustin Cauchy, Cauchy distribution, complex numbers, confidence distribution, conjecture, Don Fraser, Nancy Reid, Peter McCullagh, Sceaux, seminar, Université Paris Dauphine, William Feller on February 8, 2018 by xi'an**D**uring a visit of Don Fraser and Nancy Reid to Paris-Dauphine where Nancy gave a nice introduction to confidence distributions, Don pointed out to me a 1992 paper by Peter McCullagh on the Cauchy distribution. Following my recent foray into the estimation of the Cauchy location parameter. Among several most interesting aspects of the Cauchy, Peter re-expressed the density of a Cauchy C(θ¹,θ²) as

f(x;θ¹,θ²) = |θ²| / |x-θ|²

when θ=θ¹+ιθ² [a complex number on the half-plane]. Denoting the Cauchy C(θ¹,θ²) as Cauchy C(θ), the property that the ratio aX+b/cX+d follows a Cauchy for all real numbers a,b,c,d,

C(aθ+b/cθ+d)

[when X is C(θ)] follows rather readily. But then comes the remark that

“those properties follow immediately from the definition of the Cauchy as the ratio of two correlated normals with zero mean.”

which seems to relate to the conjecture solved by Natesh Pillai and Xiao-Li Meng a few years ago. But the fact that a ratio of two correlated centred Normals is Cauchy is actually known at least from the1930’s, as shown by Feller (1930, Biometrika) and Geary (1930, JRSS B).

## Darmois, Koopman, and Pitman

Posted in Books, Statistics with tags cross validated, Don Fraser, exponential families, George Darmois, mathematical statistics, Pitman-Koopman theorem, proof, Stanford University, sufficient statistics on November 15, 2017 by xi'an**W**hen [X’ed] seeking a simple proof of the Pitman-Koopman-Darmois lemma [that exponential families are the only types of distributions with constant support allowing for a fixed dimension sufficient statistic], I came across a 1962 Stanford technical report by Don Fraser containing a short proof of the result. Proof that I do not fully understand as it relies on the notion that the likelihood function itself is a minimal sufficient statistic.

## Bayes is typically wrong…

Posted in pictures, Running, Statistics, Travel, University life with tags Bayesian Fiducial & Frequentist Conference, Bayesian foundations, Boston, Boston harbour, Don Fraser, fiducial inference, Harvard University, matching priors, Nancy Reid, profile likelihood, skyline, sunrise on May 3, 2017 by xi'an**I**n Harvard, this morning, Don Fraser gave a talk at the Bayesian, Fiducial, and Frequentist conference where he repeated *[as shown by the above quote]* the rather harsh criticisms on Bayesian inference he published last year in Statistical Science. And which I discussed a few days ago. The “wrongness” of Bayes starts with the completely arbitrary choice of the prior, which Don sees as unacceptable, and then increases because the credible regions are not confident regions, outside natural parameters from exponential families (Welch and Peers, 1963). And one-dimensional parameters using the profile likelihood (although I cannot find a proper definition of what the profile likelihood is in the paper, apparently a plug-in version that is not a genuine likelihood, hence somewhat falling under the same *this-is-not-a-true-probability* cleaver as the disputed Bayesian approach).

“I expect we’re all missing something, but I do not know what it is.”D.R. Cox, Statistical Science, 1994

And then Nancy Reid delivered a plenary lecture *“Are we converging?”* on the afternoon that compared most principles (including objective if not subjective Bayes) against different criteria, like consistency, nuisance elimination, calibration, meaning of probability, and so on. In an highly analytic if pessimistic panorama. (The talk should be available on line at some point soon.)