scholarly journals A Bayesian Approach for Stable Distributions: Some Computational Aspects

2013 ◽  
Vol 03 (04) ◽  
pp. 268-277 ◽  
Author(s):  
Jorge A. Achcar ◽  
Sílvia R. C. Lopes ◽  
Josmar Mazucheli ◽  
Raquel R. Linhares
Keyword(s):  
Bayesian Approach ◽  
Stable Distributions ◽  
Computational Aspects

scholarly journals Linear and Non-Linear Regression Models Assuming a Stable Distribution

2016 ◽  
Vol 39 (1) ◽  
pp. 109-128 ◽  
Author(s):  
Jorge A. Achcar ◽  
Sílvia R. C. Lopes
Keyword(s):  
Probability Density Function ◽  
Linear Regression ◽  
Posterior Distribution ◽  
Regression Models ◽  
Stable Distribution ◽  
Random Variable ◽  
Stable Distributions ◽  
Linear Regression Models ◽  
Non Linear ◽  
Computational Aspects

<p>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.</p>

Sign in / Sign up

Export Citation Format

Share Document