Exact Nonparametric Tests of Orthogonality and Random Walk in the Presence of a Drift Parameter
提出了存在未知漂移参数时条件独立性和随机游走的有限样本非参数检验方法，基于同时推断，对反馈、非正态和异方差稳健，模拟显示功效不低于传统检验。
In this paper, finite-sample nonparametric tests of conditional independence and random walk are extended to allow for an unknown drift parameter. The tests proposed are based on simultaneous inference methods and remain exact in the presence of general forms of feedback, nonnormality and heterskedasticity. Further, in two simulation studies, the authors confirm that the nonparametric procedures are reliable and find that they display power comparable or superior to that of conventional tests. Copyright 1997 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.