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Bootstrap Inference×置换 (随机化) 检验×Theil-Sen 估计器×
领域统计学统计学统计学
方法族Regression modelRegression modelRegression model
起源年份197920051968
提出者Bradley EfronGood (2005); Edgington & Onghena (2007); resampling traditionHenri Theil (1950); P. K. Sen (1968)
类型Resampling-based inferenceNonparametric resampling testRobust linear regression
开创性文献Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall's Tau. Journal of the American Statistical Association, 63(324), 1379-1389. DOI ↗
别名bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımırandomization test, exact permutation test, re-randomization test, Permütasyon TestiTheil-Sen Tahmincisi, Theil-Sen regression, median slope estimator, Sen's slope estimator
相关556
摘要Bootstrap 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 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.The Theil-Sen estimator is a robust linear regression method that estimates the slope as the median of the slopes computed over all pairs of data points. Introduced by Henri Theil in 1950 and extended by P. K. Sen in 1968, it tolerates outliers in the response with a breakdown point of about 29%.
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ScholarGate方法对比: Bootstrap Inference · Permutation Test · Theil-Sen Estimator. 于 2026-06-18 检索自 https://scholargate.app/zh/compare