On 29/04/2008 8:09 AM, mad_bassie wrote:

> I'm using F-distributions :)

> I allready found some things...I could plot the qqplot as you say and that

> gives me clear results.

> Allthough I still want a clear graphic and I 'll explain it as good as I

> can...

>

> I plotted 2 graphics

> plot(density(rf(10000,2,49)))

> plot(density(disttest))

>

> (the "disttest" is a distribution i simulated myself like this:

> for(i in 1:100){

>

> X<-rnorm(50,20,4)

> Y<-rnorm(50,20,5)

> Z<-rnorm(50,20,4)

>

> vector<-c (X, Y, Z)

> vector2<-rep(c('X','Y','Z'),c(50,50,50))

> data1<-data.frame(waarde=vector, soort = vector2)

> library(mvtnorm)

>

> library(multcomp)

> data1$soort<-as.factor(data1$soort)

>

> disttest<-c(disttest,summary(aov(waarde~soort,data=data1))[[1]][1,4])

> }

> (I want to compare the theroretical F-distribution with a distribution where

> the variances are not equal...)

>

> Thos are 2 fine plots but I just can't figure out how to put them together

> in one graphic...is this possible in R...it would make things much clearer

> because the window setting are not really equal wich makes it difficult to

> compare...

You'd be better off comparing p-values than densities, but you can do

what you're trying by using lines(density(disttest)) instead of calling

plot() again.

Duncan Murdoch

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