Browsing by Author "Vidal, Ignacio"

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    Bayesian inference for dependent elliptical measurement error models
    (ELSEVIER INC, 2010) Vidal, Ignacio; Arellano Valle, Reinaldo B.
    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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    Comparison between a measurement error model and a linear model without measurement error
    (ELSEVIER, 2008) Vidal, Ignacio; Iglesias, Pilar
    The regression of a response variable y on an explanatory variable from observations on (y, x), where x is a measurement of xi, is a special case of errors-in-variables model or measurement error model (MEM). In this work we attempt to answer the following question: given the data (y, x) under a MEM, is it possible to not consider the measurement error on the covariable in order to use a simpler model? To the best of our knowledge, this problem has not been treated in the Bayesian literature. To answer that question, we compute Bayes factors, the deviance information criterion and the posterior mean of the logarithmic discrepancy. We apply these Bayesian model comparison criteria to two real data sets obtaining interesting results. We conclude that, in order to simplify the MEM, model comparison criteria can be useful to compare structural MEM and a random effect model, but we would also need other statistic tools and take into account the final goal of the model. (c) 2008 Elsevier B.V. All rights reserved.