Here is the first version of a maximum liklihood negative binomial with cluster, robust, and score options. Initial values are calculated my a call to poisson. Two scores are produced: 1) the normal B-based scores, and 2) the score based on the alpha parameter. The latter score necessitates a digamma function, which is approximated here until a formal one is developed by Statacorp. I have not added the comparison with Poisson here, but it takes only a little extra code. Otherwise, the output is the same as other ML algorithms. A caveat: if the true value of alpha is close to 0, then the model is really Poisson. There may be convergence problems. This is true with any NB type program. Actually, when modeling it is probably best to start with Poisson - and if found to be overdispersed then use the NB. The value of the robust option here is quite important. It may be quite likely that an instance of overdispersed Poisson data is not truly negative binomial either. A clustering effect, for instance, which may cause overdispersion, may not take a gamma shape. If so, then the robust options becomes important.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
file. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Publisher Info
Software component provided by Boston College Department of Economics in its series Statistical Software Components with number
S334001.
Size: Programming language: Stata Requires: Date of creation: 08 Feb 1998 Date of revision: Handle: RePEc:boc:bocode:s333901
Contact details of provider: Postal: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA Phone: 617-552-3670 Fax: +1-617-552-2308 Email: Web page: http://fmwww.bc.edu/EC/ More information through EDIRC