Võrdle meetodeid

	Jackknife'i taassalvestuse hinnang	Risti-valideerimine
Valdkond	Statistika	Otsustamine
Perekond	Hypothesis test	MCDM
Tekkeaasta	1956	1974
Looja	Maurice Henri Quenouille (bias correction); John W. Tukey (variance estimation and naming)	Stone, M.
Tüüp	Bias and variance estimation	Robustness wrapper — k-fold cross-validation for MCDM stability
Algallikas	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
Rööpnimetused	delete-one jackknife, leave-one-out jackknife, Jackknife Yeniden Örnekleme	—
Seotud	3	0
Kokkuvõte	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.