At last week's Royal Statistical Society (RSS) conference Hal Varian, Chief Economist at Google, gave a panel talk about 'Statistics at Google'. Could he get a better audience than the RSS? Hal talked about his career in academia and at Google. He remi...
Today I feel very lucky, as I have been invited to the Royal Statistical Society conference to give a tutorial on interactive web graphs with R and googleVis. I prepared my slides with RStudio, knitr, pandoc and slidy, similar to my Cambridge R talk. ...
Large-scale Inference by Brad Efron is the first IMS Monograph in this new series, coordinated by David Cox and published by Cambridge University Press. Since I read this book immediately after Cox’ and Donnelly’s Principles of Applied Statistics, I was thinking of drawing a parallel between the two books. However, while none of them can 
I have been working on a new package makeR to help manage Sweave projects where you wish to create multiple versions of documents that are based on a single source. For example, I create lots of monthly and quarterly reports using Sweave and the only differences between versions are a few variables. I have used GNU
Here is our discussion (with Nicolas Chopin) of the Read Paper of last Wednesday by T. van Erven, P. Grünwald and S. de Rooij (Centrum voor Wiskunde en Informatica, Amsterdam), entitled Catching up faster by switching sooner: a predictive approach to adaptive estimation with an application to the Akaike information criterion–Bayesian information criterion dilemma. It 
As posted in early August from JSM 2010 in Vancouver, StatProb was launched as a way to promote an on-line encyclopedia/wiki with the scientific backup of expert reviewers. This was completely novel and I was quite excited to take part in the venture as a representative of the Royal Statistical Society. Most unfortunately, the separation 
![Riemann, Langevin & Hamilton [reply]](http://www.r-bloggers.com/wp-content/uploads/2010/09/hmc_integration2.jpg?w=450&h=149)
Here is a (prompt!) reply from Mark Girolami corresponding to the earlier post: In preparation for the Read Paper session next month at the RSS, our research group at CREST has collectively read the Girolami and Calderhead paper on Riemann manifold Langevin and Hamiltonian Monte Carlo methods and I hope we will again produce a 
![StatProb [wiki]](http://www.r-bloggers.com/wp-content/uploads/2010/07/royalstat.png)
Via the support of Springer, probability and statistics societies are launching a specialised wiki called StatProb. It operates as a wiki in that authors can submit short articles on any topic, with further co-authors joining in later to improve those articles, but with the contents guaranteed via the filter of an editorial 
I already wrote about R-bloggers on the R mailing list, so it only seems fitting to write about it more here. I will explain what R-bloggers is and then move to explain what I hope it will accomplish. R-Bloggers.com is a central hub of content collected from bloggers who write about R (in English) and if
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
