Count time series with excess zeros: A Bayesian perspective using zero-adjusted distributions

Autor:	Thelma Sáfadi, Luiz Otávio De Oliveira Pala, Marcela De Marillac Carvalho
Rok vydání:	2022
Zdroj:	Semina: Ciências Exatas e Tecnológicas. 43:147-160
ISSN:	1679-0375 1676-5451
Popis:	Models for count data which are temporally correlated have been studied using many conditional distributions, such as the Poisson distribution, and the insertion of different dependence structures. Nonetheless, excess of zeros and over dispersion may be observed during the counting process and need to be considered when modelling and choosing a conditional distribution. In this paper, we propose models for counting time series using zero-adjusted distributions by inserting a dependence structure following the ARMA(p, q) process on a Bayesian framework. We perform a simulation study using the proposed Bayesian analysis and analyse the monthly time series of the number of deaths due to dengue haemorrhagic fever (ICD-A91) in Brazil.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a1ff0c2fd3cc1bed016cb36e8fb5047b https://doi.org/10.5433/1679-0375.2022v43n2p147 Zobrazit plný text záznamu