Jackknifing two-sample statistics

Edna Schechtman, Suojin Wang

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

In this paper, a new simple method for jackknifing two-sample statistics is proposed. The method is based on a two-step procedure. In the first step, the point estimator is calculated by leaving one X (or Y) out at a time. At the second step, the point estimator obtained in the first step is further jackknifed, leaving one Y (or X) out at a time, resulting in a simple formula for the proposed point estimator. It is shown that by using the two-step procedure, the bias of the point estimator is reduced in terms of asymptotic order, from O(n-1) up to O(n-2), under certain regularity conditions. This conclusion is also confirmed empirically in terms of finite sample numerical examples via a small-scale simulation study. We also discuss the idea of asymptotic bias to obtain parallel results without imposing some conditions that may be difficult to check or too restrictive in practice.

Original languageEnglish
Pages (from-to)329-340
Number of pages12
JournalJournal of Statistical Planning and Inference
Volume119
Issue number2
DOIs
StatePublished - 1 Feb 2004

Keywords

  • Bias reduction
  • Jackknife
  • Two-sample statistic
  • U-statistic

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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