So sánh phương pháp

	Ước lượng Jackknife Resampling	Cross-Validation
Lĩnh vực	Thống kê	Ra quyết định
Họ	Hypothesis test	MCDM
Năm ra đời	1956	1974
Người khởi xướng	Maurice Henri Quenouille (bias correction); John W. Tukey (variance estimation and naming)	Stone, M.
Loại	Bias and variance estimation	Robustness wrapper — k-fold cross-validation for MCDM stability
Công trình gốc	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
Tên gọi khác	delete-one jackknife, leave-one-out jackknife, Jackknife Yeniden Örnekleme	—
Liên quan	3	0
Tóm tắt	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.