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Bootstrap-Inferenz×Schätzung der mittleren absoluten Abweichung (MAD)×Permutationstest (Randomisierungstest)×
FachgebietStatistikStatistikStatistik
FamilieRegression modelRegression modelRegression model
Entstehungsjahr197919742005
UrheberBradley EfronHampel (influence-curve treatment); classical robust statisticsGood (2005); Edgington & Onghena (2007); resampling tradition
TypResampling-based inferenceRobust scale estimatorNonparametric resampling test
Wegweisende QuelleEfron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. 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 ↗Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792
Aliasnamenbootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımımedian absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahminirandomization test, exact permutation test, re-randomization test, Permütasyon Testi
Verwandt555
ZusammenfassungBootstrap 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.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.The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value.
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ScholarGateMethoden vergleichen: Bootstrap Inference · MAD Estimation · Permutation Test. Abgerufen am 2026-06-17 von https://scholargate.app/de/compare