Durbin–Watson and Generalized Durbin–Watson Tests for Autocorrelations and Randomness
推广了杜宾-沃森检验，使其能检验更高阶的自相关，并可用于随机性假设。通过匹配前两阶矩，用正态或缩放贝塔分布近似小样本下的统计量分布，且对非正态样本也适用。
The Durbin–Watson (DW) test for lag 1 autocorrelation has been generalized (DWG) to test for autocorrelations at higher lags. This includes the Wallis test for lag 4 autocorrelation. These tests are also applicable to test for the important hypothesis of randomness. It is found that for small sample sizes a normal distribution or a scaled beta distribution by matching the first two moments approximates well the null distribution of the DW and DWG statistics. The approximations seem to be adequate even when the samples are from nonnormal distributions. These approximations require the first two moments of these statistics. The expressions of these moments are derived.