[R] Simulating underdispersed counts

Gerard M. Keogh GMKeogh at justice.ie
Thu Dec 4 18:34:26 CET 2008

V interesting point Greg.

But are you not just suggesting left and right truncation?
It strikes me that if the data are Poission then a mixture is likely to be
better - something akin to zero-deflated.
Neg binomail works for greater variance == mix a gamma and poisson, but I'm
unsure what to mix to deflate the variance - maybe bernoulli.

In any event, one possibility is that the data are dependnent (e.g. family
data) so to get a underdispersion you could draw from the poisson and then
redraw from the result based on some condition such as closeness (e.g. as a
proxy for family size).

Hope this helps!

             Greg Snow                                                     
             <Greg.Snow at imail.                                             
             org>                                                       To 
             Sent by:                  René Holst <rho at aqua.dtu.dk>,       
             r-help-bounces at r-         "R-help at r-project.org"              
             project.org               <R-help at r-project.org>              
             04/12/2008 17:21                                      Subject 
                                       Re: [R] Simulating underdispersed   

Accurate probably depends on what exactly you want to accomplish with the
simulation, but one simple approach would be to generate more data than you
need from a regular Poisson distribution, then throw away the extreme
values on both sides.

Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of René Holst
> Sent: Thursday, December 04, 2008 6:40 AM
> To: R-help at r-project.org
> Subject: [R] Simulating underdispersed counts
> Hello,
> Anyone who knows a fast and accurate algorithm for generating draws
> from an underdispersed Poisson distribution. Or even better, if there
> is a package containing such an implementation.
> Thanks
> Rene
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