After writing up my tutorial regarding getting WinBUGS running on a Mac in R, a friend sent me this fantastic simple tutorial on the same thing for OpenBUGS on a mac in R. So, for those that want it, install away! Looks a good bit simpler, actually! Tweet [Read more...]

Using R I'm doing a lot of simulations of the classic monty hall-problem and plotting multiple simulations using ggplot2. [Read more...]

On Tuesday, Eric Chi and Kenneth Lange arXived a paper on a comparison of numerical techniques for solving sudokus. (The very Kenneth Lange who wrote this fantastic book on numerical analysis.) One of these techniques is the simulated annealing approach I had played with a long while ago.  They seem ... [Read more...]

I was grading my Master projects this morning and came upon this graph: which compares the variability of an importance-sampling estimator versus its self-normalised alternative… This is an interesting case in that self-normalisation does considerably degrade the quality of the approximation in that setting. In other cases, self-normalisation may bring ... [Read more...]

A few friends have asked for self-study resources on learning (or brushing up on) basic statistics. I plan to keep updating this post as I find more good suggestions. Of course the ideal case is to have a good teacher … Continue reading → [Read more...]

I know, I know, I have been kinda lame about posting here lately. But that’s because my posting muscle has been focused on the new analyses for what makes a succesful #SciFund proposal. I’ve been posting them at the #SciFund blog under the Analysis tag – so check it ... [Read more...]

I’m preparing “R101,” an introductory workshop on the statistical software R. Perhaps other beginners might find some use in the following summary and resources. (See also the post on resources for teaching yourself introductory statistics.) Do you have obligatory screenshots … Continue reading → [Read more...]

It has been a wonderful week in Roma, a mix of pleasant work and enjoyable free-time! I gave the ABC advanced course for the second time in a month so it did not require much in terms of preparation and there was a good sized audience with attentive (if too ... [Read more...]

For those who have not read the seminal works of Tufte and Cleveland, please hang your heads in shame. To salvage some sense of self-worth, you can then head over to Solomon Messing’s blog where he is starting a series on data visualization based on ... [Read more...]

Here are the R codes of the second R lab organised by Serena Arima in supplement of my lectures (now completed!). This morning I covered ABC model choice and the following example is the benchmark used in the course (and in the paper) about the impact of summary statistics. (Warning! ... [Read more...]

Much of the data that the analyst uses exhibits extraordinary range. For example: incomes, company sizes, popularity of books and any “winner takes all process”; (see: Living in A Lognormal World). Tukey recommended the logarithm as an important “stabilizing transform” (a transform that brings data into a more usable form ... [Read more...]

Ben Goldacre, the physician and biostatistician behind the always-excellent Bad Science column in the Guardian, gave a barnburner of a talk at Strata 2012 yesterday, "The Information Architecture of Medicine is Broken". For anyone not aware of the problems caused by publication bias in clinical trials (for example, ineffective drugs with ... [Read more...]

Here are the R codes of the R labs organised by Serena Arima in supplement of my lectures. This is quite impressive and helpful to the students, as illustrated by the first example below (using the abc software). I am having a great time teaching this “ABC in Roma” course, ... [Read more...]

Today, I am going to Rome for a week, teaching my PhD course on ABC I first gave in Paris. The course takes place in La Sapienza Università di Roma, from Monday till Thursday. There will be an R lab in addition to the lectures. (I have no further item ... [Read more...]

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. ... [Read more...]

You can do anything pretty easily with R, for instance, calculate concentration indexes such as the Gini index or display the Lorenz curve (dedicated to my students). Although I did not explain it during my lectures, calculating a Gini index or displaying the Lorenz curve can be done very easily ... [Read more...]

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...]

Another problem generated by X’validated (on which I spent much too much time!): given an unbiased coin that produced M heads in the first M tosses, what is the expected number of additional tosses needed to get N (N__M) consecutive heads? Consider the preliminary question of getting a ... [Read more...]

After many delays and exchanges of emails, our AMIS paper with Jean-Marie Cornuet, Jean-Michel Marin and Antonietta Mira eventually made it into the Scandinavian Journal of Statistics. I am quite glad it is now published as it will publicize the method... [Read more...]

Next Thursday (Jan. 16), at the RSS, there will be a special half-day meeting (afternoon, starting at 13:30) on Recent Advances in Monte Carlo Methods organised by the General Application Section. The speakers are Richard Everitt, University of Oxford, Missing data, and what to do about it Anthony Lee, Warwick University, Auxiliary ... [Read more...]