Data Depth Trimming Counterpart of the Classical (or ) Procedure

Yijun Zuo

Journal of Probability and Statistics, 2009, vol. 2009, 1-9

Abstract:

The classical (or in high dimensions) inference procedure for unknown mean is so fundamental in statistics and so prevailing in practices; it is regarded as an optimal procedure in the mind of many practitioners. It this manuscript we present a new procedure based on data depth trimming and bootstrapping that can outperform the classical (or in high dimensions) confidence interval (or region) procedure.

Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnljps:373572

DOI: 10.1155/2009/373572

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