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HCNBREG: Stata module to estimate Heterogeneous Canonical Negative Binomial Regression

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Joseph Hilbe ()

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Abstract

The canonical parameterization of the negative binomial derives directly from the exponential form of the negative binomial probability distribution function. Unlike the NB-2 and NB-1 parameterizations, it is not derived as a Poisson-gamma mixture model, and has the heterogeneity or ancillary parameter as a term in the mean and variance functions. However, the canonical negative binomial can be used effectively to model count response data. The Heterogeneous Canonical Negative Binomial command is similar to Stata's gnbreg command, allowing the ancillary parameter to itself be parameterized. The value of this option is that one may better understand which predictors influence model heterogeneity. That is, it assists in identifying the source of correlation in the data. The command also displays both the AIC and Deviance statistics to aid in model comparison and provides use of Stata's maximum likelihood and survey options.

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File URL: http://fmwww.bc.edu/repec/bocode/h/hcnbreg.ado
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File URL: http://fmwww.bc.edu/repec/bocode/j/jcnb_ll.ado
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Publisher Info
Software component provided by Boston College Department of Economics in its series Statistical Software Components with number S456870.

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Programming language: Stata
Requires: Stata version 9.1
Date of creation: 08 Sep 2007
Date of revision: 24 Feb 2009
Handle: RePEc:boc:bocode:s456870

Note: This module may be installed from within Stata by typing "ssc install hcnbreg". Windows users should not attempt to download these files with a web browser.
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

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Web: http://repec.org/docs/ssc.php

For technical questions regarding this item, or to correct its listing, contact: (Christopher F Baum).

Related research
Keywords: negative binomial regression; Poisson; gamma; count data;

Statistics
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This page was last updated on 2009-11-10.


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