IDEAS home Printed from

HCNBREG: Stata module to estimate Heterogeneous Canonical Negative Binomial Regression


  • Joseph Hilbe



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.

Suggested Citation

  • Joseph Hilbe, 2007. "HCNBREG: Stata module to estimate Heterogeneous Canonical Negative Binomial Regression," Statistical Software Components S456870, Boston College Department of Economics, revised 24 Feb 2009.
  • Handle: RePEc:boc:bocode:s456870 Note: This module should be installed from within Stata by typing "ssc install hcnbreg". Windows users should not attempt to download these files with a web browser.

    Download full text from publisher

    File URL:
    File Function: program code
    Download Restriction: no

    File URL:
    File Function: help file
    Download Restriction: no

    File URL:
    File Function: program code
    Download Restriction: no


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:boc:bocode:s456870. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F Baum). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.