Loading…
This event has ended. View the official site or create your own event → Check it out
This event has ended. Create your own
View analytic
Thursday, July 6 • 2:06pm - 2:24pm
**countreg**: Tools for count data regression

Sign up or log in to save this to your schedule and see who's attending!

Feedback form is now closed.
Keywords: Count data regression, model diagnostics, rootogram, visualization
Webpages: https://R-Forge.R-project.org/projects/countreg
The interest in regression models for count data has grown rather rapidly over the last 20 years, partly driven by methodological questions and partly by the availability of new data sets with complex features (see, e.g., Cameron and Trivedi 2013). The countreg package for R provides a number of fitting functions and new tools for model diagnostics. More specifically, it incorporates enhanced versions of fitting functions for hurdle and zero-inflation models that have been available via the pscl package for some 10 years (Zeileis, Kleiber, and Jackman 2008), now also permitting binomial responses. In addition, it provides zero-truncation models for data without zeros, along with mboost family generators that enable boosting of zero-truncated and untruncated count data regressions, thereby supplementing and extending family generators available with the mboost package. For visualizing model fits, countreg offers rootograms (Tukey 1972; Kleiber and Zeileis 2016) and probability integral transform (PIT) histograms. A (generic) function for computing (randomized) quantile residuals is also available. Furthermore, there are enhanced options for predict() methods. Several new data sets from a variety of fields (including dentistry, ethology, and finance) are included.
Development versions of countreg have been available from R-Forge for some time, a CRAN release is planned for summer 2017.
References Cameron, A. Colin, and Pravin K. Trivedi. 2013. Regression Analysis of Count Data. 2nd ed. Cambridge: Cambridge University Press.

Kleiber, Christian, and Achim Zeileis. 2016. “Visualizing Count Data Regressions Using Rootograms.” The American Statistician 70 (3): 296–303.

Tukey, John W. 1972. “Some Graphic and Semigraphic Displays.” In Statistical Papers in Honor of George W. Snedecor, edited by T. A. Bancroft, 293–316. Ames, IA: Iowa State University Press.

Zeileis, Achim, Christian Kleiber, and Simon Jackman. 2008. “Regression Models for Count Data in R.” Journal of Statistical Software 27 (8): 1–25. http://www.jstatsoft.org/v27/i08/.






Thursday July 6, 2017 2:06pm - 2:24pm
3.01 Wild Gallery

Attendees (153)