First-order random coefficients integer-valued threshold autoregressive processes

Han Li, Kai Yang, Shishun Zhao () and Dehui Wang
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Han Li: Jilin University
Kai Yang: Jilin University
Shishun Zhao: Jilin University
Dehui Wang: Jilin University

AStA Advances in Statistical Analysis, 2018, vol. 102, issue 3, No 1, 305-331

Abstract: Abstract In this paper, we introduce a first-order random coefficient integer-valued threshold autoregressive process, which is based on binomial thinning. Basic probabilistic and statistical properties of this model are discussed. Conditional least squares and conditional maximum likelihood estimators are derived for both the cases that the threshold variable is known or not. The asymptotic properties of the estimators are established. Moreover, forecasting problem is addressed. Finally, some numerical results of the estimates and a real data example are presented.

Keywords: Threshold integer-valued autoregressive models; Random coefficient models; Binomial thinning; Estimation; Forecasting; D-NeSS algorithm (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s10182-017-0306-3

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