[R] (no subject)

[Michael Bedward]

Hello,

One approach would be to fit your distribution using MCMC with, for
example, the rjags package. Then you can use the "zeroes trick" or
"ones trick" to implement your new distribution as described here...

http://mathstat.helsinki.fi/openbugs/data/Docu/Tricks.html

You will find a summary of Bayesian / MCMC packages here...

http://cran.r-project.org/web/views/Bayesian.html

Of these, rjags is the only one I've used directly so I can't comment
on which would be easiest. Hopefully others here can offer advice.

Michael


On 5 November 2010 00:25, Roes Da <r0ez.da at gmail.com> wrote:
> hello,i'm roesda from indonesia
> I have trouble when they have to perform parameter estimation by MLE method
> using the R programming.because, the distribution  that will be used instead
> of not like the distribution that already known distributions such as gamma
> distribution, Poisson or binomial.  the distribution that i would estimate
> the parameters are the joint distribution between the negative binomial
> distribution and Lindley. how do I translate it in R if the distribution is
> still new as I mentioned? i hope everyone can help me. thank you very much
> Simak
> Baca secara fonetik
>
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