A new INAR(1) process with bounded support for counts showing equidispersion, underdispersion and overdispersion

Yao Kang, Dehui Wang and Kai Yang
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Yao Kang: Jilin University
Dehui Wang: Jilin University
Kai Yang: Changchun University of Technology

Statistical Papers, 2021, vol. 62, issue 2, No 9, 745-767

Abstract: Abstract The present work introduces a mixture INAR(1) model based on the mixing Pegram and binomial thinning operators with a finite range $$\{0,1,\ldots ,n\}$$ { 0 , 1 , … , n } . The new model can be used to handle equidispersion, underdispersion, overdispersion, zero-inflation and multimodality. Several probabilistic and statistical properties are explored. Estimators of the model parameters are derived by the conditional maximum likelihood method. The asymptotic properties and numerical results of the estimators are also studied. In addition, the forecasting problem is addressed. Applications to real data sets are given to show the application of the new model.

Keywords: Binomial AR(1) processes; Pegram operator; Binomial thinning operator; Parameter estimation; Forecasting (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s00362-019-01111-0

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