Xi'an's Og

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 on the support of the posterior distribution represented on Figure 3.5… The R code is given as

[sourcecode gutter=”false” language=”r”]
> mean(y[,1]*apply(y,1,f)/den)/mean(apply(y,1,h)/den)
[1] 19.33745
> mean(y[,2]*apply(y,1,f)/den)/mean(apply(y,1,h)/den)
[1] 16.54468
[/sourcecode]

and should have been

[sourcecode gutter=”false” language=”r”]
> mean(y[,1]*f(y)/den)/mean(f(y)/den)
[1] 94.08314
> mean(y[,2]*f(y)/den)/mean(f(y)/den)
[1] 80.42832
[/sourcecode]

As also suggested by Brad, a similar modification applies to the remark after eqn. (3.7):

mean(apply(y,1,h)/den)

should be

mean(f(y)/den)

This entry was posted on March 3, 2011 at 12:36 am and is filed under Books, R, Statistics with tags Introducing Monte Carlo Methods with R, R, typos. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.