2007/01/02 by Xiaodong Luo, Jie Zhang, Luo, Xiaodong +8
Computer Science · Decision Sciences · Mathematics · Physics and Astronomy · #Advanced Statistical Methods and Models #Chaotic Dynamics (nlin.CD) #FOS: Physical sciences #Forecasting Techniques and Applications #Statistical and Computational Modeling #nlin.CD
paper · pdf · doi:10.48550/arxiv.nlin/0701008
arxiv created 2007/01/02 · openalex publication_date 2007/01/02 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The method of surrogate data provides a framework for testing observed data against a hierarchy of alternative hypotheses. The aim of applying this method is to exclude the possibility that the data are consistent with simple linear explanations before seeking complex nonlinear causes. However, in recent time the method has attracted considerable criticism, largely as a result of ambiguity about the formation of the underlying null hypotheses, or about the power of the chosen statistic. In this communication we show that by employing a special family of ranks statistics these problems can be avoided and the method of surrogate data placed of a firm statistical foundation.