Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. 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 hope this will be helpful for readers of “Introducing Monte Carlo Methods with R”, but, if nothing else, looking at the book from a student’s perspective has helped in uncovering typos. Here is the last batch:

– In Exercise 8.1, we need a bit more stability in the Markov chain to ensure that it has a finite variance. The assumption that both first moments are finite is not enough. Thomas Clerc from Fribourg also pointed out to me that the lazy programming  (I stole from my R course students!) of the form beta=c(beta,betaprop) should not be encouraged!

– in Example 8.9, $Y_ksimmathcal{N}(theta_i,sigma^2)$ should be $Y_isimmathcal{N}(theta_i,sigma^2)$ and the $theta_i$’s are normal, not the $mu_i$’s…

– in Exercise 8.7, it is the distribution on $alpha$ that is closed-form, not the one on $mu$.

– in Exercise 3.17, George Casella found another typo, namely that in question b it should be $X|Ysimmathcal{G}a(1,y)$, not $X|Ysimmathcal{G}a(1,y)$.

Posted in Books, R, Statistics Tagged: Introducing Monte Carlo Methods with R, MCMC, Monte Carlo methods, simulation, typos      