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Wald-Wolfowitz Runs Test×ダービン-ワトソン検定による自己相関の検出×
分野統計学計量経済学
系統Hypothesis testRegression model
提唱年19401950
提唱者Abraham Wald & Jacob WolfowitzJames Durbin & Geoffrey Watson
種類Nonparametric randomness testTest for first-order residual autocorrelation
原典Wald, A. & Wolfowitz, J. (1940). On a test whether two samples are from the same population. Annals of Mathematical Statistics, 11(2), 147–162. DOI ↗Durbin, J., & Watson, G. S. (1950). Testing for serial correlation in least squares regression: I. Biometrika, 37(3/4), 409–428. DOI ↗
別名Wald-Wolfowitz test, runs test for randomness, Runs Testi (Wald-Wolfowitz)DW test, Durbin-Watson statistic, Durbin-Watson otokorelasyon testi
関連54
概要The Wald-Wolfowitz runs test is a nonparametric hypothesis test that determines whether a sequence of observations — coded as a series of binary symbols — follows a random pattern or contains systematic structure. Introduced by Abraham Wald and Jacob Wolfowitz in 1940, the test counts the number of uninterrupted runs of identical symbols and asks whether that count is consistent with random arrangement.The 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.
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ScholarGate手法を比較: Runs Test · Durbin-Watson Test. 2026-06-18に以下より取得 https://scholargate.app/ja/compare