# Introducing Monte Carlo Methods with R

### what’s wrong with package comment?!

May 3, 2012 |

I spent most of the Sunday afternoon trying to understand why defining did not have the same effect as writing the line until I found there is a clash due to the comment package… The assuredly simple code produces an error message: This is quite an inconvenience as I need ... [Read more...]

### Example 7.17 in Introduction to Monte Carlo methods with R

January 4, 2012 |

I received the following email about Introducing Monte Carlo Methods with R a few days ago: Hallo Dr. Robert, I  am studying your fine book for myself. There´s a little problem in examples 7.17 and 8.1: in the R code a function “gu” is used and a reference given to ex. 5.17, ... [Read more...]

### Typos in Introduction to Monte Carlo Methods with R

October 12, 2011 |

The two translators of our book in Japanese, Kazue & Motohiro Ishida, contacted me about some R code mistakes in the book. The translation is nearly done and they checked every piece of code in the book, an endeavour for which I am very grateful! Here are the two issues they ... [Read more...]

### Bayesian Core and loose logs

July 26, 2011 |

Jean-Michel (aka Jean-Claude!) Marin came for a few days so that we could make late progress on the revision of our book Bayesian Core towards an Use R! version. In one of the R programs in the mixture chapter, we were getting improbable answers, until we found an R mistake ... [Read more...]

### The confusing gamma parameter

May 13, 2011 |

Boris from Ottawa sent me this email about Introducing Monte Carlo Methods with R: As I went through the exercises and examples, I believe I found a typo in exercise 6.4 on page 176 that is not in the list of typos posted on  your website.  For simulation of Gamma(a,1) random ... [Read more...]

### Another review of Introducing … R

May 2, 2011 |

The March 2011 issue of JASA contains a review of Introducing Monte Carlo Methods with R by Hedibert Lopes. As in the previous review, the poor quality of the figures is (rightly) pointed out by Hedie. However, the main message of the review remains very positive and, furthermore, Hedie advertises the ‘... [Read more...]

### Typos sorted, at last!

March 23, 2011 |

After posting so many entries about typos in my books (making you wonder how there could be any text left!) and postponing their classification for so long, I decided on Saturday afternoon to collect those entries into a comprehensive pdf document that should be more useful for readers. I incidentally ... [Read more...]

### cut&paste typo in R book

March 2, 2011 |

A casualty of cut-and-paste in Chapter 3 of Introducing Monte Carlo Methods with R. Brad McNeney from Simon Fraser sent me a nice email about the end of Example 3.6 missing a marginal estimate. Indeed, it does. And it should have been obvious from the “estimates” we derived, 19 and 16, which are not ... [Read more...]

### Introducing Monte Carlo Methods with R [precision]

January 17, 2011 |

Doug Rivers, professor of Political Sciences in Stanford, kindly sent me this email yesterday night: The 2nd displayed equation in section 2.1.2 on p. 44 is garbled (it might be interpreted as saying that U and X have the same distribution). I think you intended: And indeed we should have stated the ...

### Short review of the R book

January 5, 2011 |

David Scott wrote a review of Introducing Monte Carlo Methods with R in the International Statistical Review that is rather negative, since the main bulk reads as follows: I found some aspects of the book very disappointing. The first chapter (“Basic R Programming”) has some unfortunate mistakes and some statements, ...

### More typos in Chapter 5

December 29, 2010 |

Following Ashley’s latest comments on Chapter 5 of Introducing Monte Carlo Methods with R, I realised Example 5.5 was totally off-the-mark! Not only the representation of the likelihood should have used prod instead of mean, not only the constant should call the val argument of integrate, not only integrate  uses lower ...

### nlm [unused argument(s) (iter = 1)]

December 28, 2010 |

Ashley put the following comment on Chapter 5 of Introducing Monte Carlo Methods with R”: I am reading chapter 5. I try to reproduced the result on page 128. The R codes don’t work on my laptop. When I try to run the following codes on page 128 __ for (i in 1:(nlm(like,... [Read more...]

### Méthodes de Monte-Carlo avec R

December 2, 2010 |

The translation of the book Introducing Monte Carlo Methods with R is close to being completed. The copy-editing and page-setting are done, I have received the cover proposal and am happy with it, so it should now go to production and be ready by early January, (earlier than the tentative ... [Read more...]

### Graphical comparison of MCMC performance [arXiv:1011.445]

November 22, 2010 |

A new posting on arXiv by Madeleine Thompson on a graphical tool for assessing performance. She has developed a software called SamplerCompare, implemented in R and C. The graphical evaluation plots “log density evaluations per iteration times autocorrelation time against a tuning parameter in a grid of plots where rows ... [Read more...]

### Introducing Monte Carlo in PaRis [more slides]

November 17, 2010 |

The class started yesterday with a small but focussed and responsive audience! Given the background of the students, and in particular their clear proficiency in R!, I switched between the original slides of Introducing Monte Carlo Methods with R and those of my Monte Carlo Statistical Methods: course, updated by ... [Read more...]

### Introducing Monte Carlo in PaRis

November 14, 2010 |

As already announced on Statisfaction, I will start a short [14 hour] course in English based on Introducing Monte Carlo Methods with R at ENSAE next Tuesday. The slides were written by George Casella for a course he gave in Italy last spring and he kindly agreed on making them available ... [Read more...]

### Typos…

October 5, 2010 |

Edward Kao just sent another typo found both in  Monte Carlo Statistical Methods (Problem 3.21) and in Introducing Monte Carlo Methods with R (Exercise 3.17), namely that should be I also got another email from Jerry Sin mentioning that matrix summation in the matrix commands of Figure 1.2 of Introducing Monte Carlo Methods ...

### Effective sample size

September 23, 2010 |

In the previous days I have received several emails asking for clarification of the effective sample size derivation in “Introducing Monte Carlo Methods with R” (Section 4.4, pp. 98-100). Formula (4.3) gives the Monte Carlo estimate of the variance of a self-normalised importance sampling estimator (note the change from the original version ... [Read more...]

### Monte Carlo Statistical Methods third edition

September 23, 2010 |

Last week, George Casella and I worked around the clock on starting the third edition of Monte Carlo Statistical Methods by detailing the changes to make and designing the new table of contents. The new edition will not see a revolution in the presentation of the material but rather a ...