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Minimum volume confidence regions for a multivariate normal mean vector

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Since Stein's original proposal in 1962, a series of papers have constructed confidence regions of smaller volume than the standard spheres for the mean vector of a multivariate normal distribution. A general approach to this problem is developed here and used to calculate a lower bound on the attainable volume. Bayes and fiducial methods are involved in the calculation. Scheffé-type problems are used to show that low volume by itself does not guarantee favourable inferential properties.

Keywords: Fisher–von Mises distribution; James–Stein estimator; Non-central ; Scheffé intervals

Document Type: Research Article


Affiliations: Stanford University, USA

Publication date: 2006-09-01

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