Bayesian analysis of the p-order integer-valued AR process with zero-inflated Poisson innovations. Issue 11 (23rd July 2020)

• Record Type: Journal Article
• Authors: Garay, Aldo M.; Medina, Francyelle L.; Cabral, Celso R. B.; Lin, Tsung-I
• Is Part Of: Journal of statistical computation and simulation. Volume 90:Issue 11(2020)
• Page Start: 1943
• Page End: 1964
• Publication Date: 2020-07-23
• Subjects: Count time series -- ZINAR(p) -- Bayesian estimation -- prediction -- MCMC algorithm; 62M10; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2020.1754819
• Languages: English
• ISSNs: 0094-9655

Abstract

Abstract : In recent years, there has been a considerable interest to study count time series with a dependence structure and appearance of excess of zeros values. Such series are commonly encountered in diverse disciplines, such as economics, financial research, environmental science, public health, among others. In this paper, we propose a stationary p -order integer-valued autoregressive process with zero-inflated Poisson innovations, called the ZINAR( p ) times series model. We study some of its theoretical properties and develop a Markov chain Monte Carlo (MCMC) algorithm for inferring parameters from Bayesian perspectives. Finally, we demonstrate the utility of proposed ZINAR( p ) model through simulated and real data examples.