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

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.

Keywords:

• Larceny
• bivariate integer-valued
• CMP
• GQL