On Thu, 8 May 2008, kate wrote:
I have a data with 236 observations. After plotting the histogram, I
found that it looks like non-central t distribution. I would like to get
MLE for mu and df.
So you mean 'non-central'? See ?dt.
I found an example to find MLE for gamma distribution from "fitting distributions
with R":
library(stats4) ## loading package stats4
ll<-function(lambda,alfa) {n<-200
x<-x.gam
-n*alfa*log(lambda)+n*log(gamma(alfa))-(alfa-
1)*sum(log(x))+lambda*sum(x)} ## -log-likelihood function
est<-mle(minuslog=ll, start=list(lambda=2,alfa=1))
Is anyone how how to write down -log-likelihood function for noncentral t
distribution?
Just use dt. E.g.
library(MASS)
?fitdistr
shows you a worked example for location, scale and df, but note the
comments. You could fit a non-central t, but it would be unusual to do
so.
Thanks a lot!!
Kate
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