Bayesian Transformed GARMA Models

Breno S. Andrade; Marinho G. Andrade; Ricardo S. Ehlers

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arXiv · 1612.09561

Bayesian Transformed GARMA Models

Breno S. Andrade·Marinho G. Andrade·Ricardo S. Ehlers

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Abstract

Transformed Generalized Autoregressive Moving Average (TGARMA) models were recently proposed to deal with non-additivity, non-normality and heteroscedasticity in real time series data. In this paper, a Bayesian approach is proposed for TGARMA models, thus extending the original model. We conducted a simulation study to investigate the performance of Bayesian estimation and Bayesian model selection criteria. In addition, a real dataset was analysed using the proposed approach.

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Breno S. Andrade, Marinho G. Andrade, Ricardo S. Ehlers. 2016-12-30. Bayesian Transformed GARMA Models. https://arxiv.org/abs/1612.09561

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