विधियों की तुलना करें

	माध्यिका निरपेक्ष विचलन (MAD) आकलन	सुदृढ़ समय श्रृंखला विश्लेषण
क्षेत्र	सांख्यिकी	सांख्यिकी
परिवार	Regression model	Regression model
उद्भव वर्ष	1974	2019
प्रवर्तक	Hampel (influence-curve treatment); classical robust statistics	Maronna, Martin, Yohai & Salibián-Barrera (textbook treatment); robust estimation tradition
प्रकार	Robust scale estimator	Robust time series model (AR / MA / ARIMA)
मौलिक स्रोत	Hampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393.	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
उपनाम	median absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini	robust ARIMA, robust autoregressive model, outlier-resistant time series, Robust Zaman Serisi Analizi
संबंधित	5	5
सारांश	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.	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).