Archive for American Statistical Association

ASA opposes USDA plan likely to undermine economic research service (ERS) work [repost]

Posted in Statistics with tags , , , , , , on September 19, 2018 by xi'an

The American Statistical Association (ASA) is actively opposing a recent United States Department of Agriculture (USDA) proposal to realign and relocate the Economic Research Service (ERS). The ASA’s concern is that moving ERS—a federal statistical agency and an internationally respected agricultural economics research institution—would undermine its work and product quality, thereby also affecting evidence-based policymaking in the USDA and food and agriculture more generally.

what is your favorite teacher?

Posted in Kids, Statistics, University life with tags , , , , , , , , on October 14, 2017 by xi'an

When Jean-Louis Foulley pointed out to me this page in the September issue of Amstat News, about nominating a favourite teacher, I told him it had to be an homonym statistician! Or a practical joke! After enquiry, it dawned on me that this completely underserved inclusion came from a former student in my undergraduate Estimation course, who was very enthusiastic about statistics and my insistence on modelling rather than mathematical validation. He may have been the only one in the class, as my students always complain about not seeing the point in slides with no mathematical result. Like earlier this week when after 90mn on introducing the bootstrap method, a student asked me what was new compared with the Glivenko-Cantelli theorem I had presented the week before… (Thanks anyway to David for his vote and his kind words!)

and it only gets worse…

Posted in Kids, pictures, Travel with tags , , , , , , , , , , on April 7, 2017 by xi'an

The State Department said on Monday it was ending U.S. funding for the United Nations Population Fund, the international body’s agency focused on family planning as well as maternal and child health in more than 150 countries.Reuters, April 3, 2017

“When it comes to science, there are few winners in US President Donald Trump’s first budget proposal. The plan, released on 16 March, calls for double-digit cuts for the Environmental Protection Agency (EPA) and the National Institutes of Health (NIH). It also lays the foundation for a broad shift in the United States’ research priorities, including a retreat from environmental and climate programmes.” Nature, March 16, 2017

“In light of the recent executive order on visas and immigration, we are compelled to speak out in support of our international members. Science benefits from the free expression and exchange of ideas. As the oldest scientific society in the United States, and the world’s largest professional society for statisticians, the ASA has an overarching responsibility to support rigorous and robust science. Our world relies on data and statistical thinking to drive discovery, which thrives from the contributions of a global community of scientists, researchers, and students. A flourishing scientific culture, in turn, benefits our nation’s economic prosperity and security. ​” ASA, March, 2017

JSM 2015 [day #2]

Posted in Books, R, Statistics, Travel, University life with tags , , , , , , , , , , , , , on August 11, 2015 by xi'an

Today, at JSM 2015, in Seattle, I attended several Bayesian sessions, having sadly missed the Dennis Lindley memorial session yesterday, as it clashed with my own session. In the morning sessions on Bayesian model choice, David Rossell (Warwick) defended non-local priors à la Johnson (& Rossell) as having better frequentist properties. Although I appreciate the concept of eliminating a neighbourhood of the null in the alternative prior, even from a Bayesian viewpoint since it forces us to declare explicitly when the null is no longer acceptable, I find the asymptotic motivation for the prior less commendable and open to arbitrary choices that may lead to huge variations in the numerical value of the Bayes factor. Another talk by Jin Wang merged spike and slab with EM with bootstrap with random forests in variable selection. But I could not fathom what the intended properties of the method were… Besides returning another type of MAP.

The second Bayesian session of the morn was mostly centred on sparsity and penalisation, with Carlos Carvalho and Rob McCulloch discussing a two step method that goes through a standard posterior  construction on the saturated model, before using a utility function to select the pertinent variables. Separation of utility from prior was a novel concept for me, if not for Jay Kadane who objected to Rob a few years ago that he put in the prior what should be in the utility… New for me because I always considered the product prior x utility as the main brick in building the Bayesian edifice… Following Herman Rubin’s motto! Veronika Rocková linked with this post-LASSO perspective by studying spike & slab priors based on Laplace priors. While Veronicka’s goal was to achieve sparsity and consistency, this modelling made me wonder at the potential equivalent in our mixtures for testing approach. I concluded that having a mixture of two priors could be translated in a mixture over the sample with two different parameters, each with a different prior. A different topic, namely multiple testing, was treated by Jim Berger, who showed convincingly in my opinion that a Bayesian approach provides a significant advantage.

In the afternoon finalists of the ISBA Savage Award presented their PhD work, both in the theory and  methods section and in the application section. Besides Veronicka Rocková’s work on a Bayesian approach to factor analysis, with a remarkable resolution via a non-parametric Indian buffet prior and a variable selection interpretation that avoids MCMC difficulties, Vinayak Rao wrote his thesis on MCMC methods for jump processes with a finite number of observations, using a highly convincing completion scheme that created independence between blocks and which reminded me of the Papaspiliopoulos et al. (2005) trick for continuous time processes. I do wonder at the potential impact of this method for processing the coalescent trees in population genetics. Two talks dealt with inference on graphical models, Masanao Yajima and  Christine Peterson, inferring the structure of a sparse graph by Bayesian methods.  With applications in protein networks. And with again a spike & slab prior in Christine’s work. The last talk by Sayantan Banerjee was connected to most others in this Savage session in that it also dealt with sparsity. When estimating a large covariance matrix. (It is always interesting to try to spot tendencies in awards and conferences. Following the Bayesian non-parametric era, are we now entering the Bayesian sparsity era? We will see if this is the case at ISBA 2016!) And the winner is..?! We will know tomorrow night! In the meanwhile, congrats to my friends Sudipto Banerjee, Igor Prünster, Sylvia Richardson, and Judith Rousseau who got nominated IMS Fellows tonight.

JSM 2015 [day #1]

Posted in Books, R, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , on August 10, 2015 by xi'an

ferryThis afternoon, at JSM 2015, in Seattle, we had the Bayesian Computation I and II sessions that Omiros Papaspiliopoulos and myself put together (sponsored by IMS and ISBA). Despite this being Sunday and hence having some of the participants still arriving, the sessions went on well in terms of audience. Thanks to Mark Girolami’s strict presidency, we were so much on time in Bayesian Computation I that we had 20mn left for a floor discussion that turned into a speakers’ discussion! All talks were of obvious interest for MCMCists, but Ryan Adams’ presentation on firefly Monte Carlo got me thinking for most of the afternoon on different ways of exploiting the existence of a bound on the terms composing the target. With little to show by the end of the afternoon! On the mundane side, I was sorry to miss Pierre Jacob, who was still in France due to difficulties in obtaining a working visa for Harvard (!), and surprised to see Dawn Woodard wearing a Uber tee-shirt, until she told us she was now working at Uber! Which a posteriori makes sense, given her work on traffic predictions!