Hi Sebatiano,

Take a look at

> require(MCMCpack)
> ?MCpoissongamma

HTH,
Jorge


On Wed, Sep 21, 2011 at 5:25 AM, Sebastiano Putoto <> wrote:

> Good afternoon/morning readers. This is the first time I am trying to run
> some Bayesian computation in R, and am experiencing a few problems.
>
> I am working on a Poisson model for cancer rates which has a conjugate
> Gamma
> prior.
>
> 1) The first question is precisely how I work out the parameters.
>
> #Suppose I assign values to theta with seq()
> theta<-seq(0,1,len=500)
>
> #Then I try out the parameters that seem to fit with a certain prior idea
> on
> theta (see next)
> a=182
> b=3530
> gaprior<-dgamma(theta,a,b)
>
> It should work by trial-and-error (according to "Bayesian Computation with
> R") , but how can I check the parameters turned out well: should I just
> look
> at the plot, or evaluate it through the 1 - pgamma(x,a,b) function, having
> knowledge of the 5th percentile (data from US Cancer Statistics)?
>
> 2) Then, the next problem I have regards the likelihood distribution.
>
> #Having the react table, I name the columns (with y=deaths, and
> x=exposures)
> react
>    x  y
> 1   6 15
> 2   5 16
> 3   3 12
> 4   4  6
> 5  27 77
> 6   7 17
> 7   4 11
> 8   5 10
> 9  23 63
> 10 11 29
>
> yr <- react[,2]
> xr <- react[,1]
>
>
>
> #I then compute the likelihood
> poislike=dpois(yr, theta*xr)
>
> #And this is what I come up with, which I really don't understand.
> poislike
> [1] 0 0 0 0 0 0 0 0 0 0
>
> The values shouldn't be all null, otherwise my posterior cannot be computed
> properly. Does anyone have any idea on where I could possibly have messed
> it
> up?
>
> Thank you very much for your attention.
>
> Regards,
>
> Sebastiano Putoto (University of Pavia, Italy)
>
>        [[alternative HTML version deleted]]
>
> ______________________________________________
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> http://www.R-project.org/posting-guide.html
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>

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