A new bivariate INAR(1) model with paired Poisson-weighted exponential distributed innovations

This paper proposes a novel Bivariate integer-valued auto-regressive model of order 1 with paired Poisson Weighted Exponential (PWE) distributed innovations which is denoted by INAR(1)-PWE with two Sarmanov and classical versions. The CML and CLS estimators of the parameters are obtained and the per...

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Published inCommunications in statistics. Simulation and computation Vol. 53; no. 12; pp. 5797 - 5815
Main Authors Sajjadnia, Zahra, Sharafi, Maryam, Mamode Khan, Naushad, Soobhug, Ashwinee Devi
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 01.12.2024
Taylor & Francis Ltd
Subjects
Autoregressive models
Bivariate analysis
Bivariate new Poisson-weighted exponential distribution
Conditional maximum likelihood estimation
Innovations
Monte Carlo simulation
New weighted exponential distribution
Over-dispersion
Parameter estimation
Pearson Residuals
Sarmanov distribution
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Summary:This paper proposes a novel Bivariate integer-valued auto-regressive model of order 1 with paired Poisson Weighted Exponential (PWE) distributed innovations which is denoted by INAR(1)-PWE with two Sarmanov and classical versions. The CML and CLS estimators of the parameters are obtained and the performance of the proposed models are assessed through some Monte Carlo simulation experiments. Also, the BINAR(1)-PWE is applied to the two real data sets and is compared with some bivariate INAR processes. The research findings commend the BINAR(1)-PWE as another suitable alternative to analyze bivariate series of counts and open the avenues to explore the Sarmanov-based bivariate models.
Bibliography:ObjectType-Article-1
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content type line 14
ISSN:0361-0918
1532-4141
DOI:10.1080/03610918.2023.2199956