The summer started with a research in pair session in CiRM on the R edition of Bayesian Core, but I am also involved two other book projects. The first one was mentioned in a previous post, namely the translation of Introducing Monte Carlo Methods with R into French. I have ...

Back home after those two weeks in CiRM for our “research in pair” invitation to work on the new edition of Bayesian Core, I am very grateful for the support we received from CiRM and through it from SMF and CNRS. Being “locked” away in such a remote place brought ...

Most embarrassingly, Liaosa Xu from Virginia Tech sent the following email almost a month ago and I forgot to reply: I have a question regarding your example 7.11 in your book Introducing Monte Carlo Methods with R.  To further decompose the uniform simulation by sampling a and b step by step, ...

The function pimax from our package mcsm is used in to reproduce Figure 5.11 of our book Introducing Monte Carlo Methods with R. (The name comes from using the Pima Indian R benchmark as the reference dataset.) I got this email from Josué I ran the ‘pimax’ example from the mcsm ...

Glancing perchance at the back of my Amstat News, I was intrigued by the SAS advertisement Bayesian Methods Specify Bayesian analysis for ANOVA, logistic regression, Poisson regression, accelerated failure time models and Cox regression through the GENMOD, LIFEREG and PHREG procedures. Analyze a wider variety of models with the MCMC ...

Within the past two days, I received this email Dear Prof.Robert I have just bought your recent book on Introducing Monte Carlo Methods with R.  Although I have checked your web page for the R programs (bits of the code in the book, codes for generating the figures and ...

Springer Verlag has just posted on its webpage both the student and the instructor solution manuals to “Introducing Monte Carlo Methods with R”. Yes, both! Before you rush there, the Catch-22 in this announcement is that the access to the instructor version is restricted to registered instructors. So, if you ...

After the complete solution manual for Bayesian Core, the solution manual for the odd numbered exercises of “Introducing Monte Carlo Methods with R” is now arXived. The fuller 133 page version for instructors is available from Springer Verlag by demand only, in order to keep the appeal of the book as ...

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 ...

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 ...

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 [...]