An introduction to Bayesian analysis and why you might care. Fight club The subject of statistics is about how to learn.  Given that it is about the unknown, it shouldn’t be surprising that there are deep differences of opinion on how to go about doing it (in spite of ... [Read more...]

Being freshly elected ASA Fellow (yay!), I just received the list of 2012 ASA Fellows. Among whose, let me mention Sudipto Banerjee, University of Minnesota, Minneapolis, Minnesota, elected “For theoretical, methodological and applied research in spatiotemporal statistical modeling, especially as applied to problems in environmetrics, ecology, occupational health, agriculture and economics, ... [Read more...]

As the ‘Og reached its 1500th post and 3000th comment at exactly the same time, a wee and only mildly interesting Sunday morning foray in what was posted so far and attracted the most attention (using the statistics provided by wordpress). The most visited posts: Title Views Home page 203,727 In{... [Read more...]

Thanks to a link on R-bloggers, I was introduced to Luis Apiolaza’s blog, Quantum Forest, which covers data analyses and R comments he encounters in his research as a quantitative forester/geneticist. And he works at the University of Canterbury, Christchurch, where I first taught from Bayesian Core in 2006. ... [Read more...]

Yes, yet another Bayesian textbook: Ioannis Ntzoufras’ Bayesian modeling using WinBUGS was published in 2009 and it got an honourable mention at the 2009 PROSE Award. (Nice acronym for a book award! All the mathematics books awarded that year were actually statistics books.) Bayesian modeling using WinBUGS is rather similar to the ... [Read more...]

Here is [yet!] another Bayesian textbook that appeared recently. I read it in the past few days and, despite my obvious biases and prejudices, I liked it very much! It has a lot in common (at least in spirit) with our Bayesian Core, which may explain why I feel so ... [Read more...]

Bill Bolstad wrote a reply to my review of his book Understanding computational Bayesian statistics last week and here it is, unedited except for the first paragraph where he thanks me for the opportunity to respond, “so readers will see that the book has some good features beyond having a “... [Read more...]

I have just finished reading this book by Bill Bolstad (University of Waikato, New Zealand) which a previous ‘Og post pointed out when it appeared, shortly after our Introducing Monte Carlo Methods with R. My family commented that the cover was nicer than those of my own books, which is ... [Read more...]

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Despite not enjoying this year the optimal environment of CiRM, we are still making good progress on the revision (or the R vision) of Bayesian Core. In the past two days, we went over Chapters 1 (Introduction), 2 (Normal Models), 5 (Capture-Recapture Experiments), and 6 (Mixture Models), with Chapters 3 (Regression), 4 (Generalised Linear Models) [...] [Read more...]

I was pleasantly surprised to have my recreational reading about baseball in the New Yorker interrupted by a digression on statistics. Sam Fuld of the Tampa Bay Rays, was the subjet of a Ben McGrath profile in the 4 July 2011 issue of the New Yorker, in an article titled Super Sam. ... [Read more...]

Kent Osband writes: [Read more...]

Maximum likelihood gives the beat fit to the training data but in general overfits, yielding overly-noisy parameter estimates that don't perform so well when predicting new data. A popular solution to this overfitting problem takes advantage of the iterative nature of most maximum likelihood algorithms by stopping early. In general, ... [Read more...]

I read this article by Rivka Galchen on quantum computing. Much of the article was about an eccentric scientist in his fifties named David Deutch. I’m sure the guy is brilliant but I wasn’t particularly interested in his not particularly interesting life story (apparently he’s thin and ... [Read more...]

A couple years ago Rod Little was invited to write an article for the diamond jubilee of the Calcutta Statistical Association Bulletin. His article was published with discussions from Danny Pfefferman, J. N. K. Rao, Don Rubin, and myself. Here it all is.I'll paste my discussion below, but it's ... [Read more...]

When predicting 0/1 data we can use logit (or probit or robit or some other robust model such as invlogit (0.01 + 0.98*X*beta)). Logit is simple enough and we can use bayesglm to regularize and avoid the problem of separation. What if there are more than 2 categories? If they’re ordered (1, 2, 3, etc), [...] [Read more...]

The French agronomy research institute INRA is organising a Fall school in La Rochelle, Nov. 28 – Dec. 02, on Bayesian methods, oriented towards the applications in food sciences, environmental sciences, and biology. The provisional program (in French) is ■ Initiation aux outils informatiques R et WinBUGS (TP et réalisation de projets sur ... [Read more...]

No “That” Left Behind? I came across a post on Language Log last week giving some evidence that Obama tends to add that to the prepared version of his speeches. For example, in a recent speech at George Washington University, … Continue reading → [Read more...]

Here is an email that could appeal to some readers: Job in Cambridge MRC-BSU – Bayesian statistician Career development fellow MRC Biostatistics Unit, Cambridge We are offering an exciting opportunity to work on Bayesian models for infectious disease dynamics. A statistician is required to contribute to a programme of research to ... [Read more...]