Abstract

In this paper we introduce a new bivariate model called bivariate compound Poisson-gamma model. The corresponding variable of this model are based on compounding the Poisson number of occurrences and maximum of independent identically distributed gamma variates. For this proposed model, several distributional properties have been established. We implement the EM algorithm based on the missing value principle to find the maximum likelihood estimators. Moreover, we use the observed Fisher information matrix to construct approximate confidence intervals. The performance of the EM type algorithm is illustrated via numerical simulation studies. Finally, a natural environment data have been analyzed to see how the proposed model and the respective methods work in practice.

Citation details of the article

Journal: International Journal of Applied Mathematics
Journal ISSN (Print): ISSN 1311-1728
Journal ISSN (Electronic): ISSN 1314-8060
Volume: 34
Issue: 5
Year: 2021

DOI: 10.12732/ijam.v34i5.6

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