Bayesian linear regression with error terms that have symmetric unimod al densities
- 1 January 1995
- journal article
- research article
- Published by Taylor & Francis in Journal of Nonparametric Statistics
- Vol. 4 (4) , 335-348
- https://doi.org/10.1080/10485259508832625
Abstract
Bayes methods are provided for a multiple linear regression model in which the error terms have densities that are symmetric and unimodal at zero, but whose form is otherwise unknown. The posterior distribution of the vector of regression coefficients is obtained, as well as the predictive distribution and a Bayes estimate of the error density. A new approximation method isdescribed. A set of real data with outliers and a set of simulated data are used to compare this method to parametric methods and to an existing Monte Carlo approach.Keywords
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