Abstract
In an earlier paper (Durbin & Watson, 1950) the authors investigated the problem of testing the error terms of a regression model for serial correlation. Test criteria were put forward, their moments calculated, and bounds to their distribution functions were obtained. In the present paper these bounds are tabulated and their use in practice is described. For cases in which the bounds do not settle the question of significance an approximate method is suggested. Expressions are given for the mean and variance of a test statistic for one- and two-way classifications and polynomial trends, leading to approximate tests for these cases. The procedures described should be capable of application by the practical worker without reference to the earlier paper (hereinafter referred to as Part I).
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© 1992 Springer-Verlag New York, Inc.
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Durbin, J., Watson, G.S. (1992). Testing for Serial Correlation in Least Squares Regression. II. In: Kotz, S., Johnson, N.L. (eds) Breakthroughs in Statistics. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4380-9_21
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DOI: https://doi.org/10.1007/978-1-4612-4380-9_21
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