Robust Bayesian inference on scale parameters

Carmen Fernandez, Jacek Osiewalski and Mark Steel

Edinburgh School of Economics Discussion Paper Series from Edinburgh School of Economics, University of Edinburgh

Abstract: We represent random variables Z that take values in Re^n-{0} as Z=RY, where R is a positive random variable and Y takes values in an (n-1)-dimensional space Y. By fixing the distribution of either R or Y, while imposing independence between them, different classes of distributions on Re^n can be generated. As examples, the spherical, l[q]-spherical, v-spherical and anisotropic classes can be interpreted in this unifying framework. We present a robust Bayesian analysis on a scale parameter in the pure scale model and in the regression model. In particular, we consider robustness of posterior inference on the scale parameter when the sampling distribution ranges over classes related to those mentioned above. Some links between Bayesian and sampling-theory results are also highlighted.

Keywords: posterior distribution; scale invariance; scale model; regression model (search for similar items in EconPapers)
Pages: 15
Date: 1996
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http://www.econ.ed.ac.uk/papers/id25_esedps.pdf

Related works:
Journal Article: Robust Bayesian Inference on Scale Parameters (2001)
Working Paper: Robust Bayesian Inference on Scale Parameters (1996)
Working Paper: Robust Bayesian Inference on Scale Parameters (1996)
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Persistent link: https://EconPapers.repec.org/RePEc:edn:esedps:25

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