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Robustná analýza časových radov×Analýza bodu zlomu×
OdborŠtatistikaŠtatistika
RodinaRegression modelRegression model
Rok vzniku20191983
TvorcaMaronna, Martin, Yohai & Salibián-Barrera (textbook treatment); robust estimation traditionHampel (1971); Donoho & Huber (1983)
TypRobust time series model (AR / MA / ARIMA)Robustness diagnostic for estimators
Pôvodný zdrojMaronna, R. A., Martin, R. D., Yohai, V. J., & Salibián-Barrera, M. (2019). Robust Statistics: Theory and Methods (with R) (2nd ed.). Wiley. ISBN: 978-1119214687Donoho, D. L. & Huber, P. J. (1983). The Notion of Breakdown Point. In A Festschrift for Erich L. Lehmann (pp. 157-184). Wadsworth. link ↗
Ďalšie názvyrobust ARIMA, robust autoregressive model, outlier-resistant time series, Robust Zaman Serisi Analizibreakdown point, finite-sample breakdown point, robustness breakdown analysis, Bozunma Noktası Analizi
Príbuzné55
ZhrnutieRobust 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).Breakdown point analysis quantifies the fraction of outliers an estimator can tolerate before it produces meaningless results. Formalised by Hampel (1971) and Donoho and Huber (1983), it is the standard tool for comparing the robustness of competing estimators.
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ScholarGatePorovnať metódy: Robust Time Series Analysis · Breakdown Point Analysis. Získané 2026-06-17 z https://scholargate.app/sk/compare