Hypothesis testing for the dispersion parameter of the hyper-Poisson regression model. Issue 5 (24th March 2019)

• Record Type: Journal Article
• Authors: Santos, Daiane de Souza; Cancho, Vicente; Rodrigues, Josemar
• Is Part Of: Journal of statistical computation and simulation. Volume 89:Issue 5(2019)
• Page Start: 763
• Page End: 775
• Publication Date: 2019-03-24
• Subjects: Count data -- gradient test -- hyper-Poisson distribution -- likelihood ratio test -- Monte Carlo simulations -- overdispersion -- underdispersion; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2019.1572144
• Languages: English
• ISSNs: 0094-9655

Abstract

ABSTRACT: The Poisson distribution is widely used to deal with count data, however, it is unable to capture the dispersion problems. The hyper-Poisson distribution is a particular case of the extended Conway–Maxwell distribution which takes into account the dispersion phenomena of the count data. The main motivation to consider this model is the possibility to link the mean to the regressor variables in very natural way to solve testing problems. So, this paper will be focalized in the gradient statistics to detect dispersions and to compare with the classical likelihood ratio statistic. Two illustrative applications are considered.