Metodebevisregister

Robust Time Series Analysis

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).

Sources recorded, not reviewed

Kilderegister

Siteringer kopiert ordrett fra metodens kilderegister. Ingen påstandsnivåverifisering er underforstått fra dem.

Robust Time Series Analysis (M- and MM-estimation based AR / MA / ARIMA)

Taksonomisk metoderegister · regression-model / statistics

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
Peña, D., & Guttman, I. (1988). A Bayesian Approach for Predicting with Outliers. Journal of the American Statistical Association. · URL

Åpne full metode

Kuraterte påstander

Påstander lagret i bevishovedboken, hver med sin egen vurdering.

Ingen kuraterte påstander ennå

Denne visningen finner ikke opp en påstandsvurdering når hovedboken ikke har noen.

Relaterte metoder

Generert fra metodegrafen og vist som maskinforslåtte relasjoner – ingen bevispåstand er underforstått.

Same method familyBreakdown Point Analysismachine-suggested · Relational suggestion, not evidence.Same method familyMAD Estimationmachine-suggested · Relational suggestion, not evidence.Same method familyOLS Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyRobust Mixed Modelmachine-suggested · Relational suggestion, not evidence.Same method familySn and Qn Scale Estimatorsmachine-suggested · Relational suggestion, not evidence.