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> cau=rcauchy(10^2)
> mcau=median(cau)
> rcau=diff(quantile(cau,c(.25,.75)))/sqrt(10^2)
> f=function(x){
+ z=dcauchy(outer(x,cau,FUN="-"))
+ apply(z,1,prod)}
> fcst=integrate(f,lower=-20,upper=20)$val
> ft=function(x){f(x)/fcst}
> g=function(x){dt((x-mcau)/rcau,df=49)/rcau}
> curve(ft,from=-1,to=1,xlab="",ylab="",lwd=2)
> curve(g,add=T,lty=2,col="steelblue",lwd=2)
and the corrected Figure 5.5 is therefore as follows. Note that the fit by the t distribution is not as perfect as before. A normal approximation would do better.
This mistake is most embarrassing and I cannot fathom how I came with this unoperating program! (The more embarrassing as Cauchy‘s house is about 1k away from mine…) I am thus quite grateful to Ashley for her detailed study of this example.
Filed under: Books, R, Statistics Tagged: Cauchy distribution, integrate, Introducing Monte Carlo Methods with R, Monte Carlo Statistical Methods, simulation, typos
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