Phew!, we are now done with the solution manual in the sense that we have compiled solutions for all odd-numberedd exercises (but one!) and solved a fair number of even-numbered exercises. As it stands, the manual is 120 pages long and I am exhausted by the run to produce it over the past week. I 
Over the weekend and during the R exams, I managed to complete the solution set for Chapters 6 and 7 of “Introducing Monte Carlo Methods with R”. Chapter 6 only exhibited a few typos, despite me covering most exercises in Chapter 6, hence the merging of both chapters.
– in Exercise 6.13, both and 
After writing the solutions to the odd-numbered exercises in Chapter 5 of “Introducing Monte Carlo Methods with R”., I alas found the following typos, two of which are rather major (Exercise 5.3 and Example 5.16). I apologise to the readers these typos may confuse.
– Exercise 5.3 has no simple encompassing set and the constraint should 
Chapter 4 of “Introducing Monte Carlo Methods with R” has four typos (so far) in the exercises:
– In Exercise 4.5, the should not be in bold fonts (!)
– In Exercise 4.9, I commented too many lines when revising and thus the variance terms vanished. It should read
– In Exercise 4.13, following the removal of 
Here are two more typos in the exercises of Chapter 3 of “Introducing Monte Carlo Methods with R”.
– due to the (later) inclusion of an extra-exercise in the book, the “above exercise” in Exercise 3.5 actually means Exercise 3.3.
– in Exercise 3.11, question c, a line got commented by mistake in the LaTeX file and 
When grading homeworks for my Monte Carlo graduate class, I found that my students had pointed out two typos in the exercises of Chapter 2 of “Introducing Monte Carlo Methods with R”.
– In Exercise 2.17, question d. should be “d. Show that the maximum of is attained at .“
– In Exercise 2.21, in item 
When looking around on Amazon, I found that “Introducing Monte Carlo Methods with R” was associated with another very recently published (same day as ours!) book, “Understanding Computational Bayesian Statistics“, by William Bolstad, that seems to mostly cover the same ground as us (with some connections with Bayesian Core for prior modelling in regression and 
That’s it!, “Introducing Monte Carlo Methods with R” is out, truly out, I have received a copy from Springer by express mail today! (If you need any further proof, it is also advertised as In stock by Amazon.) Given that the printer exactly reproduces the pdf file sent to Springer, there is no element of 
Following a proposal by Springer-Verlag Paris, I have decided to translate Introducing Monte Carlo Methods with R with George Casella into French, since a new collection of R books (in French) is planed for the Spring of 2010. The translation will a priori be done by Joachim Robert and Robin Ryder, under my supervision and 
When I first read Andrew Gelman's quick off-the-cuff review of the book Bayesian Computation with R, I thought it was a bit harsh. So did Gelman.I thumbed through the book at the joint statistical meetings, and decided to buy it along with Bayesian Cor...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
