قارن الطرق

	نموذج الانحدار الذاتي المتين	المربعات الصغرى العادية (OLS) مع أخطاء معيارية قوية
المجال	الاقتصاد القياسي	الاقتصاد القياسي
العائلة	Regression model	Regression model
سنة النشأة	1986	1980
صاحب الطريقة	Martin & Yohai (influential early work); broader robust time series literature	Halbert White
النوع	Robust time series model	Linear regression with robust inference
المصدر التأسيسي	Martin, R. D., & Yohai, V. J. (1986). Influence functionals for time series. Annals of Statistics, 14(3), 781–818.	White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838.
الأسماء البديلة	robust autoregression, outlier-robust AR, M-estimator AR, heavy-tail AR	HC robust regression, White robust OLS, sandwich estimator OLS, OLS with robust standard errors
ذات صلة	6	6
الملخص	The robust AR model fits an autoregressive time series specification using estimation methods — typically M-estimators or bounded-influence estimators — that resist distortion from outliers and heavy-tailed error distributions. Unlike OLS-based AR estimation, robust variants down-weight extreme observations so that a small number of contaminated data points cannot dominate the fitted dynamics.	Robust OLS applies ordinary least squares to estimate coefficients and then replaces the classical standard errors with heteroscedasticity-consistent (HC) standard errors — commonly called White standard errors. This leaves the point estimates unchanged while yielding valid t-statistics and confidence intervals even when the error variance is not constant across observations.