Archive for Zeeman building

what have rough paths got to do with data science?

Posted in Statistics with tags , , , , , , on November 22, 2019 by xi'an

O’Bayes 2019 has now started!

Posted in pictures, Running, Statistics, Travel, University life with tags , , , , , , , , , on June 28, 2019 by xi'an

The O’Bayes 2019 conference in Warwick University has now started, with about 100 participants meeting over four days (plus one of tutorials) in the Zeeman maths building of the University. Quite a change of location and weather when compared with the previous one in Austin. As an organiser I hope all goes well at the practical level and want to thank the other persons who helped me towards this goal, first and foremost Paula Matthews who solved web and lodging and planning issues all over these past months, as well as Mark Steel and Cristiano Villa. As a member of the scientific committee, I am looking forward the talks and discussants along the coming four days, again hoping all speakers and discussants show up and are not hindered by travel or visa issues…

the new building!

Posted in pictures, Travel, University life with tags , , , , , on October 22, 2018 by xi'an

The Department of Statistics at Warwick has moved to a new MSB building, next to the Zeeman building, with a lot of light and open space, including a sort of atrium in the centre. It remains to be seen how comfortable this new glassy structure will prove, in hot and cold weather, and how it will stand the test of years (months?!). It seems the place was not designed purposely for mathematicians and statisticians, as many are complaining of the lack of blackboards (and even of whiteboards!) versus an overwhelming number of voracious screens. (Funny enough, the early video selling the building included these blackboards!) And it is unclear how so many glass panes can be contributing to the carbon neutral goal. Still, so far, I enjoyed the light and luminosity of my office, but this may change in the rare event of a grey day… (And no indoor place to store bicycles! But I did recover my bike where I had left it last time.)


LMS Invited Lecture Series / CRISM Summer School 2018

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , on July 12, 2018 by xi'an

contemporary issues in hypothesis testing

Posted in Statistics with tags , , , , , , , , , , , , , , , , , , on September 26, 2016 by xi'an

hipocontemptThis week [at Warwick], among other things, I attended the CRiSM workshop on hypothesis testing, giving the same talk as at ISBA last June. There was a most interesting and unusual talk by Nick Chater (from Warwick) about the psychological aspects of hypothesis testing, namely about the unnatural features of an hypothesis in everyday life, i.e., how far this formalism stands from human psychological functioning.  Or what we know about it. And then my Warwick colleague Tom Nichols explained how his recent work on permutation tests for fMRIs, published in PNAS, testing hypotheses on what should be null if real data and getting a high rate of false positives, got the medical imaging community all up in arms due to over-simplified reports in the media questioning the validity of 15 years of research on fMRI and the related 40,000 papers! For instance, some of the headings questioned the entire research in the area. Or transformed a software bug missing the boundary effects into a major flaw.  (See this podcast on Not So Standard Deviations for a thoughtful discussion on the issue.) One conclusion of this story is to be wary of assertions when submitting a hot story to journals with a substantial non-scientific readership! The afternoon talks were equally exciting, with Andrew explaining to us live from New York why he hates hypothesis testing and prefers model building. With the birthday model as an example. And David Draper gave an encompassing talk about the distinctions between inference and decision, proposing a Jaynes information criterion and illustrating it on Mendel‘s historical [and massaged!] pea dataset. The next morning, Jim Berger gave an overview on the frequentist properties of the Bayes factor, with in particular a novel [to me] upper bound on the Bayes factor associated with a p-value (Sellke, Bayarri and Berger, 2001)

B¹⁰(p) ≤ 1/-e p log p

with the specificity that B¹⁰(p) is not testing the original hypothesis [problem] but a substitute where the null is the hypothesis that p is uniformly distributed, versus a non-parametric alternative that p is more concentrated near zero. This reminded me of our PNAS paper on the impact of summary statistics upon Bayes factors. And of some forgotten reference studying Bayesian inference based solely on the p-value… It is too bad I had to rush back to Paris, as this made me miss the last talks of this fantastic workshop centred on maybe the most important aspect of statistics!