hi liliana: you should read the attached before doing that.
also, unrelated to above ( I think ? ), from experience, there can be
problems when you have restrictions on a parameter and then try to use gibbs
sampling to get the distribution of that parameter.
in a totally different context ( not bivariate normal ) , I tried it using
many different approaches
( gibbs, metropolis, admit ) and was never successful. good luck.
On Tue, Apr 5, 2011 at 12:23 PM, Liliana Pacheco <
liliana.pacheco24 at gmail.com> wrote:
> HI R users, perhaps you can help me with this:
>
> I am planning on using the Gibbs sampler for the correlation coefficient of
> a bivariate normal. I have a posterior distribution for rho, besides that,
> the conditional distribution for all the parameters of this posterior
> distribution. The thing is that, since I have to get a sample, size 10000
> for rho, obtain a 95% confidence interval, and repeat this procedure 1000
> times; and repeat this procedure for 50 scenaries, I'n thinking this is
> going to take forever.
>
> Is there a library for making this work faster? I've heard of
gibbs.met,
> but
> I don't know if it's going to work or even more, I didn't
understand the
> examples.
>
> Thanks!
>
> [[alternative HTML version deleted]]
>
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> PLEASE do read the posting guide
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> and provide commented, minimal, self-contained, reproducible code.
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