Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/34021
Título: Bayesian analysis of dynamic factor models using multivariate T distribution
Palavras-chave: Factor models
Gibbs samples
Multivariate t
Modelos de fator
Amostras de Gibbs
T multivariada
Data do documento: 2018
Editor: Universidade Federal de Lavras
Citação: ANDRADE, L. R. de et al. Bayesian analysis of dynamic factor models using multivariate T distribution. Revista Brasileira de Biometria, Lavras, v. 36, n. 1, p. 140-156, mar. 2018.
Resumo: The multivariate t models are symmetric and have heavier tail than the normal distribution and produce robust inference procedures for applications. In this paper, the Bayesian estimation of a dynamic factor model is presented, where the factors follow a multivariate autoregressive model, using the multivariate t distribution. Since the multivariate t distribution is complex, it was represented in this work as a mix of the multivariate normal distribution and a square root of a chi-square distribution. This method allowed the complete dene of all the posterior distributions. The inference on the parameters was made taking a sample of the posterior distribution through a Gibbs Sampler. The convergence was veried through graphical analysis and the convergence diagnostics of Geweke (1992) and Raftery and Lewis (1992).
URI: http://www.biometria.ufla.br/index.php/BBJ/article/view/155
http://repositorio.ufla.br/jspui/handle/1/34021
Aparece nas coleções:DES - Artigos publicados em periódicos

Arquivos associados a este item:
Não existem arquivos associados a este item.


Os itens no repositório estão protegidos por copyright, com todos os direitos reservados, salvo quando é indicado o contrário.