An X’idated reader of Monte Carlo Statistical Methods had trouble with our Example 3.13, the very one our academic book reviewer disliked so much as to “diverse [sic] a 2 star”. The issue is with computing the integral when f is the Student’s t(5) distribution density. In our book, we ... [Read more...]

One of my students wrote the following code for his R exam, trying to do accept-reject simulation (of a Rayleigh distribution) and constant approximation at the same time: which I find remarkable if alas doomed to fail! I wonder if there exists a (real as opposed to fantasy) computer language ... [Read more...]

(This post is the preliminary version of a book review by Alessandra Iacobucci, to appear in CHANCE. Enjoy [both the review and the book]!) As Rob J. Hyndman enthusiastically declares in his blog, “this is a gem of a book”. I would go even further and argue that The Art ... [Read more...]

As mentioned in the latest post on ABC, I am giving a short doctoral course on ABC methods and convergence at CREST next week. I have now made a preliminary collection of my slides (plus a few from Jean-Michel Marin’s), available on slideshare (as ABC in Roma, because I ... [Read more...]

In the revision of Bayesian Core on which Jean-Michel Marin and I worked together most of last week, having missed our CIRM break last summer (!), we have now included an illustration of what happens to an AR(p) time series when the customary stationarity+causality condition on the roots of ... [Read more...]

Another arXiv posting I had had no time to comment is Nial Friel’s and Jason Wyse’s “Estimating the model evidence: a review“. This is a review in the spirit of two of our papers, “Importance sampling methods for Bayesian discrimination between embedded models” with Jean-Michel Marin (published in ... [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...]

I received the following email about Introducing Monte Carlo Methods with R a few days ago: Hallo Dr. Robert, I  am studying your fine book for myself. There´s a little problem in examples 7.17 and 8.1: in the R code a function “gu” is used and a reference given to ex. 5.17, ... [Read more...]

Around Christmas time I presented my first impressions of Kruschke’s Doing Bayesian Data Analysis. This is a very nice book but one of its drawbacks was that part of the code used BUGS, which left mac users like me stuck. … Continue reading → [Read more...]

About a month ago I was discussing the approach that I would like to see in introductory Bayesian statistics books. In that post I mentioned a PDF copy of Doing Bayesian Data Analysis by John K. Kruschke and that I … Continue reading → [Read more...]

For those who did not know, Stanford university offered free off charge 3 courses at beginning of the autumn. It is kind of shocking – US based institution offers education for free! Take any socialism oriented country and one of the promises is education for free. But it seems, that the argument ... [Read more...]

During the summer I was contacted by a hedge fund from Bahamas. The fund was looking for someone with R language skills on-site and insisted for phone interview. Besides obvious questions about finance, statistics, coding and how many tennis balls can fit in Boeing 747 (ok, this question was omitted), they ... [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...]

This post is somewhat marginal to R in that there are several statistical systems that could be used to tackle the problem. Bayesian statistics is one of those topics that I would like to understand better, much better, in fact. … Continue reading → [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...]

I just got the “news” that Dennis Ritchie died, although this happened on October 12… The announcement was surprisingly missing from my information channels and certainly got little media coverage, compared with Steve Jobs‘ demise. (I did miss the obituaries in the New York Times and in the Guardian. The Economist ... [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...]

During a short if profitable visit to Dublin for a SFI meeting on Tuesday/Friday, I had the opportunity to visit the National Gallery of Ireland in my sole hour of free time (as my classy hotel was very close). The building itself is quite nice, being well-inserted between brick ... [Read more...]

“Bayes Theorem is a simple consequence of the axioms of probability, and is therefore accepted by all as valid. However, some who challenge the use of personal probability reject certain applications of Bayes Theorem.“  J. Kadane, p.44 Principles of uncertainty by Joseph (“Jay”) Kadane (Carnegie Mellon University, Pittsburgh) is a ... [Read more...]