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	सुदृढ़ समय श्रृंखला विश्लेषण	Sn and Qn Scale Estimators
क्षेत्र	सांख्यिकी	सांख्यिकी
परिवार	Regression model	Regression model
उद्भव वर्ष	2019	1993
प्रवर्तक	Maronna, Martin, Yohai & Salibián-Barrera (textbook treatment); robust estimation tradition	Rousseeuw & Croux
प्रकार	Robust time series model (AR / MA / ARIMA)	Robust scale estimator
मौलिक स्रोत	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	Rousseeuw, P. J., & Croux, C. (1993). Alternatives to the Median Absolute Deviation. Journal of the American Statistical Association, 88(424), 1273-1283.
उपनाम	robust ARIMA, robust autoregressive model, outlier-resistant time series, Robust Zaman Serisi Analizi	Sn estimator, Qn estimator, Rousseeuw-Croux scale estimators, robust scale estimation
संबंधित	5	5
सारांश	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).	Sn and Qn are robust estimators of scale (spread) proposed by Rousseeuw and Croux (1993) as alternatives to the median absolute deviation (MAD). Both attain a 50% breakdown point while delivering higher statistical efficiency than MAD, so they measure dispersion accurately even when the data contain outliers.