Abstract

ACHCAR, JORGE A.  and  LOPES, SÍLVIA R. C.. Linear and Non-Linear Regression Models Assuminga Stable Distribution. Rev.Colomb.Estad. [online]. 2016, vol.39, n.1, pp.109-128. ISSN 0120-1751.

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.

Keywords : Stable Laws; Bayesian Analysis; Mcmc Methods; OpenBUGS Software.

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