Abstract

This paper presents the parameter estimation and the simultaneous testing for the parameters of a modified multivariate generalized Poisson regression (MGPR) model that takes into account a measure of exposure and defines the correlation as a function of covariates. An exposure is included in the model to account for population size difference of the analysis units in the study where the exposure is not necessarily the same for each response variable. The correlations between the response variable are defined as a function of the covariates with the assumption that each response variable and their correlations are affected by the same covariates. The Newton method with BHHH algorithm is used to obtain maximum likelihood estimators of the modified MGPR model. The test statistic G2 for simultaneous hypothesis testing is achieved using the likelihood ratio method which is asymptotically chi-square distributed with v degrees of freedom.

Original languageEnglish
Title of host publicationProceedings of the 8th SEAMS-UGM International Conference on Mathematics and Its Applications 2019
Subtitle of host publicationDeepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations
EditorsHerni Utami, Fajar Adi Kusumo, Nanang Susyanto, Yeni Susanti
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735419438
DOIs
Publication statusPublished - 19 Dec 2019
Event8th SEAMS-UGM International Conference on Mathematics and Its Applications 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations - Yogyakarta, Indonesia
Duration: 29 Jul 20191 Aug 2019

Publication series

NameAIP Conference Proceedings
Volume2192
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference8th SEAMS-UGM International Conference on Mathematics and Its Applications 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations
Country/TerritoryIndonesia
CityYogyakarta
Period29/07/191/08/19

Keywords

  • BHHH algorithm
  • Exposure
  • Multivariate Generalized Poisson Regression

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