Comparer des méthodes

	Estimation par jackknife	Validation croisée
Domaine	Statistique	Prise de décision
Famille	Hypothesis test	MCDM
Année d'origine	1956	1974
Auteur d'origine	Maurice Henri Quenouille (bias correction); John W. Tukey (variance estimation and naming)	Stone, M.
Type	Bias and variance estimation	Robustness wrapper — k-fold cross-validation for MCDM stability
Source fondatrice	Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353–360.	Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society Series B
Alias	delete-one jackknife, leave-one-out jackknife, Jackknife Yeniden Örnekleme	—
Apparentées	3	0
Résumé	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.	CROSS-VALIDATION (Cross-Validation — k-fold hold-out validation of MCDM decision consistency) is a ranking multi-criteria decision-making (MCDM) method introduced by Stone, M. in 1974. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.