Minimum message length shrinkage estimation

Enes Makalic; Daniel F. Schmidt

doi:10.1016/j.spl.2008.12.021

Minimum message length shrinkage estimation

Enes Makalic, Daniel F. Schmidt

Research output: Contribution to journal › Article › Research › peer-review

7 Citations (Scopus)

Abstract

This note considers estimation of the mean of a multivariate Gaussian distribution with known variance within the Minimum Message Length (MML) framework. Interestingly, the resulting MML estimator exactly coincides with the positive-part James-Stein estimator under the choice of an uninformative prior. A new approach for estimating parameters and hyperparameters in general hierarchical Bayes models is also presented. Crown

Original language	English
Pages (from-to)	1155-1161
Number of pages	7
Journal	Statistics and Probability Letters
Volume	79
Issue number	9
DOIs	https://doi.org/10.1016/j.spl.2008.12.021
Publication status	Published - 2009

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10.1016/j.spl.2008.12.021

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JO - Statistics and Probability Letters

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Minimum message length shrinkage estimation

Abstract

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