Posts Tagged ‘ Introducing Monte Carlo Methods with R ’

what’s wrong with package comment?!

May 3, 2012
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what’s wrong with package comment?!

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 to compile my solution manual

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Example 7.17 in Introduction to Monte Carlo methods with R

January 4, 2012
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Example 7.17 in Introduction to Monte Carlo methods with R

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, but I cann´t

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Typos in Introduction to Monte Carlo Methods with R

October 12, 2011
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Typos in Introduction to Monte Carlo Methods with R

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 have noticed (after incorporating

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Bayesian Core and loose logs

July 26, 2011
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Bayesian Core and loose logs

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 in the shape of which

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The confusing gamma parameter

May 13, 2011
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The confusing gamma parameter

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 variables with  candidate distribution

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Another review of Introducing … R

May 2, 2011
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Another review of Introducing … R

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 ‘Og itself in the

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Typos sorted, at last!

March 23, 2011
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Typos sorted, at last!

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 noticed that my book web-page

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cut&paste typo in R book

March 2, 2011
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cut&paste typo in R book

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 even

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Introducing Monte Carlo Methods with R [precision]

January 17, 2011
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Introducing Monte Carlo Methods with R [precision]

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 implicit convention that

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Short review of the R book

January 5, 2011
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Short review of the R book

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, which are contentious at least

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