Multivariate mixed Poisson Generalized Inverse Gaussian INAR(1) regression

Chen, Zezhun, Dassios, Angelos ORCID: 0000-0002-3968-2366 and Tzougas, George (2022) Multivariate mixed Poisson Generalized Inverse Gaussian INAR(1) regression. Computational Statistics. ISSN 0943-4062

Text (Dassios_multivariate-mixed-poisson-generalized-inverse-gaussian--published) - Published Version Available under License Creative Commons Attribution. Download (1MB)

• Author
• Scopus publication

Abstract

In this paper, we present a novel family of multivariate mixed Poisson-Generalized Inverse Gaussian INAR(1), MMPGIG-INAR(1), regression models for modelling time series of overdispersed count response variables in a versatile manner. The statistical properties associated with the proposed family of models are discussed and we derive the joint distribution of innovations across all the sequences. Finally, for illustrative purposes different members of the MMPGIG-INAR(1) class are fitted to Local Government Property Insurance Fund data from the state of Wisconsin via maximum likelihood estimation.

Item Type:	Article
Official URL:	https://www.springer.com/journal/180
Additional Information:	© 2022 The Authors
Divisions:	Statistics
Subjects:	H Social Sciences > HA Statistics
Date Deposited:	15 Jun 2022 09:15
Last Modified:	19 Dec 2024 00:46
URI:	http://eprints.lse.ac.uk/id/eprint/115369

Actions (login required)

View Item