Modeling time series of counts with a new class of INAR(1) model
Article Type
Research Article
Publication Title
Statistical Papers
Abstract
This paper presents a new model for a stationary non-negative first order of integer-valued random variables based on the Pegram and thinning operators. Some fundamental and regression properties of the proposed model are discussed. Maximum likelihood estimation (MLE) by the EM algorithm is applied to estimate the parameters. Numerical studies to compare the proposed model with the thinning and Pegram models and the breakdown point of MLE for the proposed model have been conducted. Finally, a real life count data set has been used to illustrate its application. Comparison with existing models by AIC showed that the proposed model is much better and illustrates its potential usefulness in empirical modeling.
First Page
393
Last Page
416
DOI
10.1007/s00362-015-0704-0
Publication Date
6-1-2017
Recommended Citation
Khoo, Wooi Chen; Ong, Seng Huat; and Biswas, Atanu, "Modeling time series of counts with a new class of INAR(1) model" (2017). Journal Articles. 2568.
https://digitalcommons.isical.ac.in/journal-articles/2568