Bayesian inference for dependent elliptical measurement error models
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Date
2010
Journal Title
Journal ISSN
Volume Title
Publisher
ELSEVIER INC
Abstract
In this article we provide a Bayesian analysis for dependent elliptical measurement error models considering nondifferential and differential errors. In both cases we compute posterior distributions for structural parameters by using squared radial prior distributions for the precision parameters. The main result is that the posterior distribution of location parameters, for specific priors, is invariant with respect to changes in the generator function, in agreement with previous results obtained in the literature under different assumptions. Finally, although the results obtained are valid for any elliptical distribution for the error term, we illustrate those results by using the student-t distribution and a real data set. (c) 2010 Elsevier Inc. All rights reserved.
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Keywords
Bayesian inference, Dependent measurement error model, Elliptical distribution, INFLUENTIAL OBSERVATIONS, VARIABLES, OUTLIERS