Count time series with excess zeros: A Bayesian perspective using zero-adjusted distributions
| Autor: | Luiz Otávio de Oliveira Pala, Marcela de Marillac Carvalho, Thelma Sáfadi |
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| Jazyk: | English<br />Portuguese |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Semina: Ciências Exatas e Tecnológicas, Vol 43, Iss 2 (2022) |
| Druh dokumentu: | article |
| ISSN: | 1679-0375 1676-5451 |
| DOI: | 10.5433/1679-0375.2022v43n2p147 |
| 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: | Directory of Open Access Journals |
| Externí odkaz: |
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