Negative binomial time series models based on expectation thinning operators

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Negative binomial time series models based on expectation thinning operators

TitleNegative binomial time series models based on expectation thinning operators
Publication TypeJournal Article
Year of Publication2010
AuthorsZhu, R, Joe, H
JournalJournal of Statistical Planning and Inference
Volume140
Pagination1874-1888
Date PublishedJUL
Type of ArticleArticle
ISSN0378-3758
KeywordsAutoregressive, Binomial thinning, Generalized discrete self-decomposability, Inversion of characteristic function, Negative binomial time series, Self-generalizability
AbstractThe study of count data time series has been active in the past decade, mainly in theory and model construction. There are different ways to construct time series models with a geometric autocorrelation function, and a given univariate margin such as negative binomial. In this paper, we investigate negative binomial time series models based on the binomial thinning and two other expectation thinning operators, and show how they differ in conditional variance or heteroscedasticity. Since the model construction is in terms of probability generating functions, typically, the relevant conditional probability mass functions do not have explicit forms. In order to do simulations, likelihood inference, graphical diagnostics and prediction, we use a numerical method for inversion of characteristic functions. We illustrate the numerical methods and compare the various negative binomial time series models for a real data example. (C) 2010 Elsevier B.V. All rights reserved.
DOI10.1016/j.jspi.2010.01.031