A Note on Bootstrap Variance Estimation

Abstract

The bootstrap estimator of the asymptotic covariance matrix of a function of sample means or sample quantiles is inconsistent in some situations. A modified bootstrap estimator is proposed and shown to be consistent under weak conditions. A simulation study shows that in terms of finite-sample performance, the improvement of this modification is substantial. The computation of this modified bootstrap estimator is much easier and cheaper than that of the estimator based on the quantiles of the bootstrap distribution. It is shown by simulation that with the same number of bootstrap replicates (in bootstrap Monte Carlo approximation), the modified bootstrap estimator is more accurate than the estimator based on the interquartile range of the bootstrap distribution.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1988
Accession Number
ADA204266

Entities

People

  • Jun Shao

Organizations

  • Purdue University

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Computations
  • Consistency
  • Contracts
  • Covariance
  • Data Science
  • Distribution Functions
  • Estimators
  • Information Science
  • Military Research
  • Normal Distribution
  • Simulations
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Inference
  • Statistics
  • Universities

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.