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Odhad pomocí jackknife metody×Křížová validace×
OborStatistikaRozhodování
RodinaHypothesis testMCDM
Rok vzniku19561974
TvůrceMaurice Henri Quenouille (bias correction); John W. Tukey (variance estimation and naming)Stone, M.
TypBias and variance estimationRobustness wrapper — k-fold cross-validation for MCDM stability
Původní zdrojQuenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353–360. DOI ↗Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society Series B DOI ↗
Další názvydelete-one jackknife, leave-one-out jackknife, Jackknife Yeniden Örnekleme
Příbuzné30
ShrnutíJackknife 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.
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ScholarGatePorovnat metody: Jackknife Estimation · CROSS-VALIDATION. Získáno 2026-06-15 z https://scholargate.app/cs/compare