Nonparametric Tests of Randomness Against Autocorrelated Normal Alternatives
推导了针对自相关正态备择假设的局部最优秩检验，考虑了自回归和移动平均备择假设，证明了统计量在随机性假设下渐近正态，并通过蒙特卡洛方法比较了小样本检验功效。
Locally most powerful rank tests of randomness against autocorrelated normal alternatives are derived. In particular, autoregressive and moving average alternatives are considered. The distribution of the statistic under the hypothesis of randomness is shown to be asymptotically normal. The small sample power of the test procedure is compared with that of two other procedures by the Monte Carlo Method.