Dear Dr. Dalgaard,

Thank you for your insight! In fact, I did read the example documentation, however, it pretty much told me the same thing that my little simulation did: there is ALOT of point mass at zero. 

Is there any fix to this problem? Seeing that rgamma won't work accurately, if I wanted to plot a density of an inverse gamma distribution with small scale and shape parameters, how would I do so?

Peter Dalgaard <p.dalgaard@biostat.ku.dk> wrote: Gregory Gentlemen wrote:
> Hello fellow R users,
>
> I wanted to view the density on the standard deviation scale of a gamma(0.001, 0.001) prior for the precision. I did this as seen in the code below and found that for some reason rgamma is giving many values equal to zero, which is strange since a gamma distribution is continuous. What is going on here?
>
> Thanks for any help in advance.
> Greg
>   
That sort of shape parameter gives a distribution with most of its mass 
squashed against the y axis, so random numbers underflow to zero. But 
why did you not read the Example section of help(rgamma)? The effect is 
clearly indicated there.

>   
>> x1 <- rgamma(10000, shape=0.001, scale=0.001)
>> sd1 <- 1/sqrt(x1)
>> truehist(sd1, xlim=c(0, 1.5))
>>     
> Error in truehist(sd1, xlim = c(0, 1.5)) : 
>         'nbins' must result in a positive integer
>   
>> summary(sd1)
>>     
>       Min.    1st Qu.     Median       Mean    3rd Qu.       Max. 
>  2.266e+01  9.311e+66 3.250e+153        Inf        Inf        Inf 
>
>
>        
> ---------------------------------
>
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>
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>   


-- 
   O__  ---- Peter Dalgaard             Øster Farimagsgade 5, Entr.B
  c/ /'_ --- Dept. of Biostatistics     PO Box 2099, 1014 Cph. K
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