Autor(en): | Wurp, Hendrik van der Groll, Andreas Kneib, Thomas Marra, Giampiero Radice, Rosalba |
Titel: | Generalised joint regression for count data |
Sonstige Titel: | a penalty extension for competitive settings |
Sprache (ISO): | en |
Zusammenfassung: | 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. |
Schlagwörter: | Count data regression Joint modelling Competitive settings Regularisation Football |
URI: | http://hdl.handle.net/2003/40103 http://dx.doi.org/10.17877/DE290R-21980 |
Erscheinungsdatum: | 2020-06-25 |
Rechte (Link): | https://creativecommons.org/licenses/by/4.0/ |
Enthalten in den Sammlungen: | Fakultät für Statistik |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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VanDerWurp2020_Article_GeneralisedJointRegressionForC.pdf | 780.49 kB | Adobe PDF | Öffnen/Anzeigen |
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