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ブートストラップ推論×中央絶対偏差 (MAD) 推定×頑健時系列分析×
分野統計学統計学統計学
系統Regression modelRegression modelRegression model
提唱年197919742019
提唱者Bradley EfronHampel (influence-curve treatment); classical robust statisticsMaronna, Martin, Yohai & Salibián-Barrera (textbook treatment); robust estimation tradition
種類Resampling-based inferenceRobust scale estimatorRobust time series model (AR / MA / ARIMA)
原典Efron, 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 ↗Maronna, R. A., Martin, R. D., Yohai, V. J., & Salibián-Barrera, M. (2019). Robust Statistics: Theory and Methods (with R) (2nd ed.). Wiley. ISBN: 978-1119214687
別名bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımımedian absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahminirobust ARIMA, robust autoregressive model, outlier-resistant time series, Robust Zaman Serisi Analizi
関連555
概要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.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.Robust Time Series Analysis fits autoregressive, moving-average, and ARIMA models to series that contain outliers or structural breaks, using M-estimation or MM-estimation instead of ordinary least squares so that a few anomalous observations do not distort the fit. It follows the robust statistics tradition consolidated in Maronna, Martin, Yohai and Salibián-Barrera (2019).
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ScholarGate手法を比較: Bootstrap Inference · MAD Estimation · Robust Time Series Analysis. 2026-06-17に以下より取得 https://scholargate.app/ja/compare