First-order integer-valued autoregressive process with Markov-switching coefficients. Issue 13 (16th June 2022)

• Record Type: Journal Article
• Authors: Lu, Feilong; Wang, Dehui
• Is Part Of: Communications in statistics. Volume 51:Issue 13(2022)
• Page Start: 4313
• Page End: 4329
• Publication Date: 2022-06-16
• Subjects: INAR -- Markov-switching model -- maximum likelihood estimation -- thinning operation; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2020.1813302
• Languages: English
• ISSNs: 0361-0926

Abstract

Abstract: A class of integer-valued autoregressive models is considered, which are based on a latten process e.g., a Markov chain. Some statistical properties of this class of models are discussed. Moreover, parameter estimation and forecasting are addressed. A Monte Carlo simulation study is conducted to examine the finite sample performance of the given estimation procedure. Finally, the performance of these models is illustrated by empirical applications to two sets of real counts.