QRMlib has routines for fitting t distributions. Have a look at that
package. Also sn has routines for skew-t distributions
David Scott
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.
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?
Thanks a lot!!
Kate
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_________________________________________________________________
David Scott Department of Statistics, Tamaki Campus
The University of Auckland, PB 92019
Auckland 1142, NEW ZEALAND
Phone: +64 9 373 7599 ext 86830 Fax: +64 9 373 7000
Email: [EMAIL PROTECTED]
Graduate Officer, Department of Statistics
Director of Consulting, Department of Statistics
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