Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Análise Robusta de Séries Temporais× | Análise do Ponto de Ruptura× | |
|---|---|---|
| Área | Estatística | Estatística |
| Família | Regression model | Regression model |
| Ano de origem≠ | 2019 | 1983 |
| Autor original≠ | Maronna, Martin, Yohai & Salibián-Barrera (textbook treatment); robust estimation tradition | Hampel (1971); Donoho & Huber (1983) |
| Tipo≠ | Robust time series model (AR / MA / ARIMA) | Robustness diagnostic for estimators |
| Fonte seminal≠ | 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 | Donoho, D. L. & Huber, P. J. (1983). The Notion of Breakdown Point. In A Festschrift for Erich L. Lehmann (pp. 157-184). Wadsworth. link ↗ |
| Outros nomes | robust ARIMA, robust autoregressive model, outlier-resistant time series, Robust Zaman Serisi Analizi | breakdown point, finite-sample breakdown point, robustness breakdown analysis, Bozunma Noktası Analizi |
| Relacionados | 5 | 5 |
| Resumo≠ | 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). | 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. |
| ScholarGateConjunto de dados ↗ |
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