On Sun, 18 Nov 2007, Gregory Gentlemen wrote:
> 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?
You haven't understood the issue snown in the example. This is not about
'won't work accurately', but 'can't work accurately': half the mass is on
numbers which cannot be represented in your computer.
and Vincent Goulet wrote
> Package actuar has the {d,p,q,r}invgamma() functions (and quite a few
> others), if this can be of any help to you.
But it cannot, because the reciprocals cannot be represented either (and
actually the issue is a little worse because there is no gradual
overflow). And indeed that is what happens if you try the suggestion.
> Peter Dalgaard <[EMAIL PROTECTED]> 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
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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