Bayesian R-estimates in two-sample location models |
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Authors: | Xiaojiang Zhan Thomas P Hettmansperger |
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Affiliation: | a Merck & Co., Inc., RY34-A316, 126 E. Lincoln Avenue, P.O. Box 2000, Rahway, NJ 07065, USA b Department of Statistics, The Pennsylvania State University, University Park, PA 16802, USA |
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Abstract: | Implementation of nonparametric rank-based procedures in the Bayesian context is discussed primarily for the two-sample location models. The information in the data is summarized via the (possibly asymptotic) distribution of some rank-based quantity, which is used as a pseudo-likelihood. The complete posterior distribution (or the posterior distribution up to a normalizing constant) of the parameter of interest given the rank-based quantity can be obtained by assuming a prior distribution for the parameter. Statistical inference then proceeds based on this posterior distribution. Posterior estimation and testing are considered, along with a discussion of a normal approximation to the posterior distribution. |
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Keywords: | Robust estimate Bayesian analysis Rank estimate Two-sample location model |
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