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Bootstrap Inference×Robustní analýza časových řad×
OborStatistikaStatistika
RodinaRegression modelRegression model
Rok vzniku19792019
TvůrceBradley EfronMaronna, Martin, Yohai & Salibián-Barrera (textbook treatment); robust estimation tradition
TypResampling-based inferenceRobust time series model (AR / MA / ARIMA)
Původní zdrojEfron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. 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
Další názvybootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımırobust ARIMA, robust autoregressive model, outlier-resistant time series, Robust Zaman Serisi Analizi
Příbuzné55
ShrnutíBootstrap 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.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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ScholarGatePorovnat metody: Bootstrap Inference · Robust Time Series Analysis. Získáno 2026-06-17 z https://scholargate.app/cs/compare