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Journal of the American Statistical Association Volume 95, 2000 - Issue 452
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Theory and Method

A Simpler, Affine-Invariant, Multivariate, Distribution-Free Sign Test

Ronald H. Randles Department of Statistics, University of Florida, Gainesville, FL, 32611, USA
Pages 1263-1268 | Received 01 Aug 1999, Published online: 17 Feb 2012
 
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Abstract

A simpler multivariate sign test is proposed that uses the transformation-retransformation approach of Chakraborty, Chaudhuri, and Oja together with a directional transformation due to Tyler. This produces a multivariate sign test that is practical to apply to data of any dimension, makes minimal assumptions about the underlying distribution, and has a small-sample distribution-free property over a broad class of population models. It is shown to perform very well in comparison to Hotelling's T 2 and other multivariate sign tests for heavy-tailed and skewed distributions.

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