Type I multivariate Pólya-Aeppli distributions with applications
Claire Geldenhuys, René Ehlers, Andriëtte Bekker
Abstract
Open-access reader
Claire Geldenhuys, René Ehlers, Andriëtte Bekker
Abstract
Open-access reader
An extensive body of literature exists that specifically addresses the univariate case of zero-inflated count models. In contrast, research pertaining to multivariate models is notably less developed. We proposed two new parsimonious multivariate models which can be used to model correlated multivariate overdispersed count data. Furthermore, for different parameter settings and sample sizes, various simulations are performed. In conclusion, we demonstrated the performance of the newly proposed multivariate candidates on two benchmark datasets, which surpasses that of several alternative approaches.
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An extensive body of literature exists that specifically addresses the univariate case of zero-inflated count models. In contrast, research pertaining to multivariate models is notably less developed. We proposed two new parsimonious multivariate models which can be used to model correlated multivariate overdispersed count data. Furthermore, for different parameter settings and sample sizes, various simulations are performed. In conclusion, we demonstrated the performance of the newly proposed multivariate candidates on two benchmark datasets, which surpasses that of several alternative approaches.
Key concepts: Multivariate statistics, Univariate, Multivariate analysis, Benchmark (surveying), Contrast (vision), Computer science, Count data, Statistics