Browsing by Author "Branco, M"

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    Bayesian analysis of the calibration problem under elliptical distributions
    (ELSEVIER SCIENCE BV, 2000) Branco, M; Bolfarine, H; Iglesias, P; Arellano Valle, RB
    In this paper we discuss calibration problems under dependent and independent elliptical family of distributions. In the dependent case, it is shown that the posterior distribution of the quantity of interest is robust with respect to the distributions in the elliptical family. In particular, the results obtained by Hoadley (1970. J. Amer. Statist. 65, 356-369) showing that the inverse estimator is a Bayes estimator under normal models with a Student-t prior also holds under the dependent elliptical family of distributions. In the independent case, the use of the elliptical family allows the consideration of models which provide protection against possible outliers in the data. The multivariate calibration problem is also considered, where some results given in Brown (1993. Measurement, Regression and Calibration. Oxford University Press, Oxford) are extended. Finally, the results of the paper are applied to a real data problem, showing that the Student-t model can be a valid alternative to normality. (C) 2000 Elsevier Science B.V. All rights reserved.
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    Bayesian calibration under a student-t model
    (SPRINGER HEIDELBERG, 1998) Branco, M; Bolfarine, H; Iglesias, P
    In this paper we consider linear calibration problems in regressions models with independent errors distributed according to the Student-t distribution. The approach followed is Bayesian, thus, involving the need for the specification of prior distributions for the model parameters. It is shown that the problem is equivalent to considering an heteroscedastic regression model with an appropriate prior distributions on the model variances. By considering this alternative construction for the Student-t calibration model it is possible to use the Gibbs sampler to estimate the marginal posterior distributions. Simulation studies are reported which illustrate the performance of the approach proposed. An application to a data set analyzed by Smith and Corbett (1987) on measuring marathon courses is considered by using the approach developed in the paper.