This may sound like a paradoxical title given my recent production in this area of ABC approximations, especially after the disputes with Alan Templeton, but I have come to the conclusion that ABC approximations to the Bayes factor are not to be trusted. When working one afternoon in Park City with Jean-Michel and Natesh Pillai 
This my first post in 2011. this post has cost me a bit more than usual, but I hope it meets expectations. The aim of this tutorial is to generate an algorithm based on black box trading, with all the necessary elements for evaluation. That is a first post of several, in order to explore the problems, features of...
This my first post in 2011. this post has cost me a bit more than usual, but I hope it meets expectations. The aim of this tutorial is to generate an algorithm based on black box trading, with all the necessary elements for evaluation. That is a first post of several, in order to explore the problems, features of...
I should have probably figured this out a long time ago, but as I get deeper into programming with R, I am finding the need to remove all rows from a dataframe. I was making this alot harder than it had to be. your.df<- your.df Replace your.df with, your dataframe and you are good 
The text below went out as a post to the r-packages list a few days ago, but I thought it would make sense to post it on the blog too. So with a little html markup... Summary Version 0.9.0 of the Rcpp package is now on CRAN and its mirrors. Thi...
I have just completed my first Reproducible Research Compendium "Analysis of the combined survey datasets from the American Red Cross Tsunami Recovery Program Psycho-Social Project (adult community respondents)". It is basically all the repo...
I will be running a workshop on Statistical Forecasting: Principles and Practice in Switzerland, 20-22 June 2011. Check out the venue: Waldhotel Doldenhorn, Kandersteg! So if you fancy a trip to the beautiful Swiss Alps next June, read on… Outline Forecasting is required in many situations: deciding whether to build another power generation plant in
SOME EMPIRICAL BASES FOR CHOOSING CERTAIN RISK REPRESENTATIONS OVER OTHERS This week DSN posts some thoughts (largely inspired by the work of former colleagues Stephanie Kurzenhäuser, Ralph Hertwig, Ulrich Hoffrage, and Gerd Gigerenzer) about communicating risks to the general public, providing references and delicious downloads where possible. Representations to use less often Single-event probabilities as
An obvious omission in my previous post on Great-circle distance calculations in R was a lack of discussion on the computational efficiency of the various methods, and in particular comparing different implementations of the same method. One of the comments … Continue reading →
![Graphical comparison of MCMC performance [arXiv:1011.445]](http://www.r-bloggers.com/wp-content/uploads/2010/11/fig-cpu.jpg?w=200&h=269)
A new posting on arXiv by Madeleine Thompson on a graphical tool for assessing performance. She has developed a software called SamplerCompare, implemented in R and C. The graphical evaluation plots “log density evaluations per iteration times autocorrelation time against a tuning parameter in a grid of plots where rows represent distributions and columns represent 
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
