手法を比較

	ジャックナイフ法による推定	順列検定（ランダム化検定）
分野	統計学	統計学
系統	Hypothesis test	Regression model
提唱年	1956	2005
提唱者	Maurice Henri Quenouille (bias correction); John W. Tukey (variance estimation and naming)	Good (2005); Edgington & Onghena (2007); resampling tradition
種類	Bias and variance estimation	Nonparametric resampling test
原典	Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353–360.	Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792
別名	delete-one jackknife, leave-one-out jackknife, Jackknife Yeniden Örnekleme	randomization test, exact permutation test, re-randomization test, Permütasyon Testi
関連	3	5
概要	Jackknife estimation is a classical resampling technique that computes the bias and variance of a statistical estimator by systematically leaving out one observation at a time and re-computing the statistic on each reduced sample. Introduced by Maurice Quenouille in 1956 for bias correction and extended by John Tukey in 1958 who coined the name, it is the historical predecessor of the bootstrap and remains analytically tractable for smooth, differentiable estimators.	The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value.