Analysis of Count Time Series: A Bayesian GARMA(p, q) Approach
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Published:2023-09-11
Issue:5
Volume:52
Page:131-151
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ISSN:1026-597X
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Container-title:Austrian Journal of Statistics
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language:
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Short-container-title:AJS
Author:
Pala Luiz Otávio de Oliveira,Carvalho Marcela de M.,Sáfadi Thelma
Abstract
Extensions of the Autoregressive Moving Average, ARMA(p, q), class for modeling non-Gaussian time series have been proposed in the literature in recent years, being applied in phenomena such as counts and rates. One of them is the Generalized Autoregressive Moving Average, GARMA(p, q), that is supported by the Generalized Linear Models theory and has been studied under the Bayesian perspective. This paper aimed to study models for time series of counts using the Poisson, Negative binomial and Poisson inverse Gaussian distributions, and adopting the Bayesian framework. To do so, we carried out a simulation study and, in addition, we showed a practical application and evaluation of these models by using a set of real data, corresponding to the number of vehicle thefts in Brazil.
Publisher
Austrian Statistical Society
Subject
Applied Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability