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Estimativa por Jackknife×Validação Cruzada×
ÁreaEstatísticaTomada de decisão
FamíliaHypothesis testMCDM
Ano de origem19561974
Autor originalMaurice Henri Quenouille (bias correction); John W. Tukey (variance estimation and naming)Stone, M.
TipoBias and variance estimationRobustness wrapper — k-fold cross-validation for MCDM stability
Fonte seminalQuenouille, 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 ↗
Outros nomesdelete-one jackknife, leave-one-out jackknife, Jackknife Yeniden Örnekleme
Relacionados30
ResumoJackknife 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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ScholarGateComparar métodos: Jackknife Estimation · CROSS-VALIDATION. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare