# Typo in Chapter 5

September 9, 2010
By

(This article was first published on Xi'an's Og » R, and kindly contributed to R-bloggers)

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

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

Tags: , , , , , , , , ,