학술논문

A new thinning-based INAR(1) process for underdispersed or overdispersed counts
Document Type
Article
Source
Journal of the Korean Statistical Society, 49(2), pp.324-349 Jun, 2020
Subject
통계학
Language
English
ISSN
2005-2863
1226-3192
Abstract
Underdispersed and overdispersed phenomena are often observed in practice. To deal with these phenomena, we introduce a new thinning-based integer-valued autoregressive process. Some probabilistic and statistical properties of the process are obtained. The asymptotic normality of the estimators of the model parameters, using conditional least squares, weighted conditional least squares and modified quasi-likelihood methods, are presented. One overdispersed real-data example and one underdispersed real-data example are given to show the flexibility and superiority of the new model.