[R] MLE for noncentral t distribution

[kate]

Thanks for your quick reply.

I try the command as follows,

library(stats4) ## loading package stats4
ll <- function(change, ncp, df) {-sum(dt(x, ncp=ncp, df=df, 
log=TRUE))}#-log-likelihood function
est<-mle(minuslog=ll, start=list(ncp=-0.3,df=2))

But the warnings appears as follows,

invalid class "mle" object: invalid object for slot "fullcoef" in class 
"mle": got class "list", should be or extend class "numeric"

When I typed warnings(), I get

In dt(x, ncp = ncp, df = df, log = TRUE) :
  full precision was not achieved in 'pnt'

Does anyone know how to solve it?

Thanks,

Kate


----- Original Message ----- 
From: "Duncan Murdoch" <murdoch at stats.uwo.ca>
To: "kate" <yhsu6 at uiuc.edu>
Cc: <r-help at r-project.org>
Sent: Thursday, May 08, 2008 9:46 AM
Subject: Re: [R] MLE for noncentral t distribution


> On 5/8/2008 10:34 AM, 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?
>
>
> dt() has a non-centrality parameter and a log parameter, so it would 
> simply be
>
> ll <- function(x, ncp, df) sum(dt(x, ncp=ncp, df=df, log=TRUE))
>
> Make sure you convert mu into the ncp properly; the man page says how ncp 
> is interpreted.
>
> Duncan Murdoch