Linganisha mbinu

	Makadirio ya Jackknife Resampling	Cross-Validation
Nyanja	Takwimu	Ufanyaji Maamuzi
Familia	Hypothesis test	MCDM
Mwaka wa asili	1956	1974
Mwanzilishi	Maurice Henri Quenouille (bias correction); John W. Tukey (variance estimation and naming)	Stone, M.
Aina	Bias and variance estimation	Robustness wrapper — k-fold cross-validation for MCDM stability
Chanzo asilia	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
Majina mbadala	delete-one jackknife, leave-one-out jackknife, Jackknife Yeniden Örnekleme	—
Zinazohusiana	3	0
Muhtasari	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.