Comparison of bootstrap and jackknife variance estimators in linear regression: Second order results

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

In an extension of the work of Liu and Singh (1992), we consider resampling estimates for the variance of the least squares estimator in linear regression models. Second order terms in asymptotic expansions of these estimates are derived. By comparing the second order terms, certain generalised bootstrap schemes are seen to be theoretically better than other resampling techniques under very general conditions. The performance of the different resampling schemes are studied through a few simulations.

Original languageEnglish (US)
Pages (from-to)575-598
Number of pages24
JournalStatistica Sinica
Volume12
Issue number2
StatePublished - Apr 1 2002

Fingerprint

Jackknife
Variance Estimator
Resampling
Linear regression
Bootstrap
Least Squares Estimator
Term
Linear Regression Model
Estimate
Asymptotic Expansion
Estimator
Simulation

Keywords

  • Bootstrap
  • Jackknife
  • Regression
  • Variance comparison

Cite this

Comparison of bootstrap and jackknife variance estimators in linear regression : Second order results. / Bose, Arup; Chatterjee, Snigdhansu.

In: Statistica Sinica, Vol. 12, No. 2, 01.04.2002, p. 575-598.

Research output: Contribution to journalArticle

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