Authors: Wurp, Hendrik van der
Groll, Andreas
Kneib, Thomas
Marra, Giampiero
Radice, Rosalba
Title: Generalised joint regression for count data
Other Titles: a penalty extension for competitive settings
Language (ISO): en
Abstract: We propose a versatile joint regression framework for count responses. The method is implemented in the R add-on package GJRM and allows for modelling linear and non-linear dependence through the use of several copulae. Moreover, the parameters of the marginal distributions of the count responses and of the copula can be specified as flexible functions of covariates. Motivated by competitive settings, we also discuss an extension which forces the regression coefficients of the marginal (linear) predictors to be equal via a suitable penalisation. Model fitting is based on a trust region algorithm which estimates simultaneously all the parameters of the joint models. We investigate the proposal’s empirical performance in two simulation studies, the first one designed for arbitrary count data, the other one reflecting competitive settings. Finally, the method is applied to football data, showing its benefits compared to the standard approach with regard to predictive performance.
Subject Headings: Count data regression
Joint modelling
Competitive settings
Issue Date: 2020-06-25
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Appears in Collections:Fakultät für Statistik

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