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آزمون دوربین-واتسون برای خودهمبستگی×حداقل مربعات تعمیم‌یافته (GLS)×
حوزهاقتصادسنجیآمار
خانوادهRegression modelRegression model
سال پیدایش19501935
پدیدآورJames Durbin & Geoffrey WatsonAlexander Craig Aitken
نوعTest for first-order residual autocorrelationLinear estimator
منبع بنیادینDurbin, J., & Watson, G. S. (1950). Testing for serial correlation in least squares regression: I. Biometrika, 37(3/4), 409–428. DOI ↗Aitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48. DOI ↗
نام‌های دیگرDW test, Durbin-Watson statistic, Durbin-Watson otokorelasyon testiGLS, Aitken estimator, EGLS, feasible GLS
مرتبط43
خلاصهThe Durbin-Watson test, developed by James Durbin and Geoffrey Watson in 1950–1951, detects first-order serial correlation in the residuals of a linear regression. Its statistic ranges from 0 to 4, with a value near 2 indicating no autocorrelation, values toward 0 indicating positive autocorrelation, and values toward 4 indicating negative autocorrelation. It remains one of the most reported regression diagnostics despite well-known limitations.Generalized Least Squares (GLS) is a linear regression estimator that extends ordinary least squares to handle situations where the error terms are correlated or have non-constant variance (heteroscedasticity). Introduced by Alexander Craig Aitken in 1935, GLS achieves the Best Linear Unbiased Estimator (BLUE) under a general error covariance structure by weighting observations according to their precision, providing a theoretical bridge between OLS and modern linear mixed models.
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ScholarGateمقایسهٔ روش‌ها: Durbin-Watson Test · Generalized Least Squares. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare