论文信息 - THE DURBIN-WATSON TEST FOR SERIAL CORRELATION WHEN THERE IS NO INTERCEPT IN THE REGRESSION

THE DURBIN-WATSON TEST FOR SERIAL CORRELATION WHEN THERE IS NO INTERCEPT IN THE REGRESSION

and where tl, 2, ... , n-k is a set of independent standard normal variates. The significance points of dM, dL, and du may be evaluated by the methods of Imhof [3] and Pan [8]. Savin and White [9] have noted that Koerts and Abrahamse's [5, pp. 159-160] FORTRAN implementation of Imhof's procedure fails to converge when the significance point is near A1. This defect is easily remedied by replacing Imhof's lower bound for the inverse of the truncation error by

R. Farebrother | R W Farebrother

[1] Wilford L. L'Esperance,et al. An Algorithm for Determining the Distribution Function of the Durbin-Watson Test Statistic , 1976 .

[2] J. Durbin,et al. Testing for serial correlation in least squares regression. II. , 1950, Biometrika.

[3] J. Imhof. Computing the distribution of quadratic forms in normal variables , 1961 .

[4] R. W. Farebrother,et al. Pan's Procedure for the Tail Probabilities of the Durbin–Watson Statistic , 1980 .

[5] Giselbert Kramer. On the Durbin-Watson Bounds Test in the Case of Regression Through the Origin , 1971 .

[6] Kenneth J. White,et al. THE DURBIN-WATSON TEST FOR SERIAL CORRELATION WITH EXTREME SAMPLE SIZES OR MANY REGRESSORS' , 1977 .

[7] J. Sargan,et al. On the theory and application of the general linear model , 1970 .