Regression model

Jackknife Resampling

The jackknife is a classical resampling method that estimates the bias and variance of a statistic by systematically recomputing it with one observation left out at a time. Introduced by Quenouille in 1956 and later reviewed by Miller in 1974, it predates the bootstrap and remains a simple, deterministic tool for assessing estimator stability.

StatMind ile uygulaSoonVideoSoon

Tam yöntemi oku

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353-360. DOI: 10.1093/biomet/43.3-4.353
  2. Miller, R. G. (1974). The Jackknife — A Review. Biometrika, 61(1), 1-15. DOI: 10.1093/biomet/61.1.1

Related methods

Referenced by

ScholarGateJackknife (Jackknife Resampling). Retrieved 2026-06-04 from https://scholargate.app/tr/statistics/jackknife