Linear and non-linear regression models assuming a stable distribution
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2016Tipo
Outro título
Modelos de regressión lineal y no lineal suponiendo una distribución estable
Assunto
Abstract
In this paper, we present some computational aspects for a Bayesian analysis involving stable distributions. It is well known that, in general, there is no closed form for the probability density function of a stable distribution. However, the use of a latent or auxiliary random variable facilitates obtaining any posterior distribution when related to stable distributions. To show the usefulness of the computational aspects, the methodology is applied to linear and non-linear regression models. ...
In this paper, we present some computational aspects for a Bayesian analysis involving stable distributions. It is well known that, in general, there is no closed form for the probability density function of a stable distribution. However, the use of a latent or auxiliary random variable facilitates obtaining any posterior distribution when related to stable distributions. To show the usefulness of the computational aspects, the methodology is applied to linear and non-linear regression models. Posterior summaries of interest are obtained using the OpenBUGS software. ...
Resumen
Contido em
Revista Colombiana de Estadistica. Bogotá. Vol. 39, no. 1 (Jan. 20016), p. 109-128
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Estrangeiro
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Artigos de Periódicos (39351)Ciências Exatas e da Terra (5974)
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