Larceny trend in some areas of Mauritius via a bivariate INAR(1) model with dispersed COM-Poisson innovations

Yuvraj SunecherDepartment of Accounting, Finance and Economics, University of Technology, Port Louis, Mauritius; Correspondence[email protected]

Naushad Mamode KhanDepartment of Economics and Statistics, University of Mauritius, Reduit, Mauritius;

Ibrahim KoodoruthDepartment of Social Studies, University of Mauritius, Reduit, Mauritius;

Zeinab JannooDepartment of Economics and Statistics, University of Mauritius, Reduit, Mauritius;

Smita RampatDepartment of Social Studies, University of Mauritius, Reduit, Mauritius;

Vandna JowaheerDepartment of Mathematics, University of Mauritius, Reduit, Mauritius;

Mohammad ArashiDepartment of Statistics, Faculty of Mathematical Sciences, Shahrood University of Technology, Shahrood, Islamic Republic of Iran

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Abstract

This article addresses the modelling of day and night larceny incidents in two regions of Mauritius through a bivariate integer-valued autoregressive of order 1 (BINAR(1)) model with a flexible Conway–Maxwell Poisson (CMP) innovations under time-varying moments. The outcome of the study demonstrates scientifically the contributory effects and helps to understand the main influential factors which could guide policy makers for remedial measures. A small simulation study is also incorporated to assess the performance of the generalized quasi-likelihood (GQL) estimation method. The proposed model is compared with other relevant competing bivariate models in the application part.

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Larceny trend in some areas of Mauritius via a bivariate INAR(1) model with dispersed COM-Poisson innovations

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Larceny trend in some areas of Mauritius via a bivariate INAR(1) model with dispersed COM-Poisson innovations

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