Just saw this nice review of R for dummies. And thought after this afternoon class that my students in the simulation course at Paris-Dauphine could clearly benefit from reading it! They in fact had a terrible time simulating a truncated normal distribution by accept-reject. As they could not get the notion of normalising constants… (Yes, 
Among the books I received for review in CHANCE, here are some neither I nor my “usual suspects” had enough time or interest in to review: R Graphics (second edition) by Paul Murrell Biostatistics: A computing approach by Stewart Anderson Advanced Bayesian methods for medical test accuracy by Lyle Broemeling Introduction to Probability with Texas 
After a sunny weekend to unpack and unwind, I am now back to my normal schedule, on my way to Paris-Dauphine for an R (second-chance) exam. Except for confusing my turn signal for my wiper, thanks to two weeks of intensive driving in four Australian states!, things are thus back to “normal”, meaning that I 
Check them out. Here are thirty homoskedastic ones: > homo.wiener for (j in 1:30) { for (i in 2:length(homo.wiener)) { homo.wiener for (j in 1:30) { plot( homo.wiener, type = "l", col = rgb(.1,....
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
