On Estimation of the Bivariate Poisson INAR Process

In a recent article, Pedeli and Karlis ( 2010 ) examined the extension of the classical Integer-valued Autoregressive (INAR) model to the bivariate case. In the present article, we examine estimation methods for the case of bivariate Poisson innovations. This is a simple extension of the classical I...

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Bibliographic Details
Published inCommunications in statistics. Simulation and computation Vol. 42; no. 3; pp. 514 - 533
Main Authors Pedeli, Xanthi, Karlis, Dimitris
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis Group 01.03.2013
Taylor & Francis Ltd
Subjects
BINAR model
Bivariate Poisson distribution
Computation
Computer simulation
Correlation
Count data
Discrete valued time series
Estimators
Primary 62M10
Secondary 62F99
Studies
Time series
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Summary:In a recent article, Pedeli and Karlis ( 2010 ) examined the extension of the classical Integer-valued Autoregressive (INAR) model to the bivariate case. In the present article, we examine estimation methods for the case of bivariate Poisson innovations. This is a simple extension of the classical INAR model allowing for two discrete valued time series to be correlated. Properties of different estimators are given. We also compare their properties via a small simulation experiment. Extensions to incorporate covariate information is discussed. A real data application is also provided.
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ISSN:0361-0918
1532-4141
DOI:10.1080/03610918.2011.639001