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	सुदृढ़ समय श्रृंखला विश्लेषण	माध्यिका निरपेक्ष विचलन (MAD) आकलन
क्षेत्र	सांख्यिकी	सांख्यिकी
परिवार	Regression model	Regression model
उद्भव वर्ष	2019	1974
प्रवर्तक	Maronna, Martin, Yohai & Salibián-Barrera (textbook treatment); robust estimation tradition	Hampel (influence-curve treatment); classical robust statistics
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	Hampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393.
उपनाम	robust ARIMA, robust autoregressive model, outlier-resistant time series, Robust Zaman Serisi Analizi	median absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini
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).	Median Absolute Deviation estimation is a robust measure of statistical dispersion that replaces the standard deviation when outliers are present. Rooted in the influence-curve framework formalised by Hampel (1974), it summarises the spread of a continuous variable using medians instead of means, so a single extreme value cannot distort the result.