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Gilles Guillot from Technical University of Denmark taught a course based on our R book and he pointed out to me several typos in Chapter 5 of “Introducing Monte Carlo Methods with R”:

• p.137 second equation from bottom

$h(theta+beta zeta) - h(theta+beta zeta)$

should be

$h(theta+beta zeta) - h(theta-beta zeta)$

[right, another victim of cut-and-paste]

• p. 138  Example 5.7 denominator in the gradient should be 2*beta [yes, the error actually occurs twice. And once again in the R code]
• p. 138 : First paragraph Not a typo but a lack of details: are the conditions on $alpha$ and $beta$ necessary and sufficient? [indeed, they are sufficient]
• demo(Chapter.5) triggers an error message [true, the shortcut max=TRUE instead of maximise=TRUE in optimise does not work with R version 2.11.1]

I checked the last item with the new version of R and got the following confirmation that optimise does not accept (any longer) the abbreviation of its arguments…

demo(Chapter.5)
————————

Type     to start :

> # Section 5.1, Numerical approximation
>
> ref=rcauchy(5001)

> f=function(y){-sum(log(1+(x-y)^2))}

> mi=NULL

> for (i in 1:400){
+   x=ref[1:i]
+   aut=optimise(f,interval=c(-10,10),max=T)
+   mi=c(mi,aut$max) + } Error in f(arg, …) : unused argument(s) (max = TRUE) > optimise(f,interval=c(-10,10),maximum=T)$maximum
[1] -2.571893

\$objective
[1] -6.661338e-15

Filed under: Books, R, Statistics Tagged: birthday, Gilles Guillot, Introducing Monte Carlo Methods with R, optimise, R 2.11.1, R syntax, typo