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부트스트랩 추론×잭나이프 재표본 추출×중앙값 절대 편차 (MAD) 추정×
분야통계학통계학통계학
계열Regression modelRegression modelRegression model
기원 연도197919561974
창시자Bradley EfronQuenouille (1956); reviewed by Miller (1974)Hampel (influence-curve treatment); classical robust statistics
유형Resampling-based inferenceResampling / bias and variance estimationRobust scale estimator
원전Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353-360. DOI ↗Hampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393. DOI ↗
별칭bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımıleave-one-out resampling, Quenouille-Tukey jackknife, delete-one jackknife, Jackknife Yeniden Örneklememedian absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini
관련555
요약Bootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requires no distributional assumption and produces reliable confidence intervals even in small samples.The jackknife is a classical resampling method that estimates the bias and variance of a statistic by systematically recomputing it with one observation left out at a time. Introduced by Quenouille in 1956 and later reviewed by Miller in 1974, it predates the bootstrap and remains a simple, deterministic tool for assessing estimator stability.Median Absolute Deviation estimation is a robust measure of statistical dispersion that replaces the standard deviation when outliers are present. Rooted in the influence-curve framework formalised by Hampel (1974), it summarises the spread of a continuous variable using medians instead of means, so a single extreme value cannot distort the result.
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ScholarGate방법 비교: Bootstrap Inference · Jackknife · MAD Estimation. 2026-06-17에 다음에서 검색함: https://scholargate.app/ko/compare