| Autor: |
Andrade, Marinho G., Ehlers, Ricardo S., Andrade, Breno S. |
| Rok vydání: |
2015 |
| Předmět: |
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| Zdroj: |
Communications in Statistics: Case Studies, Data Analysis and Applications, 1 (2016) 192-205 |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1080/23737484.2016.1190307 |
| Popis: |
Generalized autoregressive moving average (GARMA) models are a class of models that was developed for extending the univariate Gaussian ARMA time series model to a flexible observation-driven model for non-Gaussian time series data. This work presents Bayesian approach for GARMA models with Poisson, binomial and negative binomial distributions. A simulation study was carried out to investigate the performance of Bayesian estimation and Bayesian model selection criteria. Also three real datasets were analysed using the Bayesian approach on GARMA models. |
| Databáze: |
arXiv |
| Externí odkaz: |
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