Lab Home | Phone | Search
Center for Nonlinear Studies  Center for Nonlinear Studies
 Home 
 People 
 Current 
 Affiliates 
 Visitors 
 Students 
 Research 
 ICAM-LANL 
 Publications 
 Conferences 
 Workshops 
 Sponsorship 
 Talks 
 Colloquia 
 Colloquia Archive 
 Seminars 
 Postdoc Seminars Archive 
 Quantum Lunch 
 Quantum Lunch Archive 
 CMS Colloquia 
 Q-Mat Seminars 
 Q-Mat Seminars Archive 
 P/T Colloquia 
 Archive 
 Kac Lectures 
 Kac Fellows 
 Dist. Quant. Lecture 
 Ulam Scholar 
 Colloquia 
 
 Jobs 
 Postdocs 
 CNLS Fellowship Application 
 Students 
 Student Program 
 Visitors 
 Description 
 Past Visitors 
 Services 
 General 
 
 History of CNLS 
 
 Maps, Directions 
 CNLS Office 
 T-Division 
 LANL 
 
Wednesday, August 07, 2019
10:00 AM - 11:00 AM
CNLS Conference Room (TA-3, Bldg 1690)

Seminar

Flexible Regression Models for Dispersed Count Data

Kimberly Sellers
Georgetown University

Poisson regression is a popular tool for modeling count data and is applied in a vast array of applications across disciplines. Real data, however, are often over- or under-dispersed relative to the Poisson model, and thus are not conducive to Poisson regression. This talk presents a regression model based on the Conway-Maxwell-Poisson (COM-Poisson or CMP) distribution which serves as a flexible alternative that contains both the Poisson and logistic regressions as special cases, and can handle other count data with a range of dispersion levels. We discuss model estimation, inference, diagnostics etc. for both the standard CMP regression and its zero-inflated analog, and introduce the associated R package, COMPoissonReg, developed to aid analysts with such data.

To meet with the speaker: Contact Emily Casleton, ecasleton@lanl.gov

Upcoming invited seminars:
8/14: Laura Freeman, Virginia Tech
8/21: Mark Glickman, Harvard University
8/28: Trisalyn Nelson, Arizona State University
9/12: David van Dyk, Imperial College London

Host: Invited Statistical Sciences Seminar Series (CCS-6)