Abstract
The main object of this paper is to discuss Bayesian inference in elliptical measurement error models. We consider dependent and independent elliptical models. Some general results are obtained for the class of dependent elliptical models. Weak nondifferential and differential models are investigated. One special submodel is the Student-t family. Given the complexity of some of the independent models considered, we make use of Monte Carlo Markov chain techniques to make inference on the parameters of interest. An application to a real data set is considered to illustrate some of the main results of the chapter.
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