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잭나이프 추정×몬테카를로 시뮬레이션×
분야통계학의사결정
계열Hypothesis testMCDM
기원 연도19561949
창시자Maurice Henri Quenouille (bias correction); John W. Tukey (variance estimation and naming)Metropolis, N., Ulam, S.
유형Bias and variance estimationRobustness wrapper — Monte Carlo uncertainty propagation
원전Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353–360. DOI ↗Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
별칭delete-one jackknife, leave-one-out jackknife, Jackknife Yeniden Örnekleme
관련30
요약Jackknife 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.MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGate방법 비교: Jackknife Estimation · MONTE-CARLO-SIMULATION. 2026-06-17에 다음에서 검색함: https://scholargate.app/ko/compare