替代数据方法是检验时间序列非线性和混沌的重要统计方法，应用此方法时，常用的检验统计量各有优势与局限性。本文在采用振幅调节傅立叶变换法(AAFT)产生替代数据后，引入信息冗余度作为检验统计量进行统计检验，研究了单变量及多变量的非线性定性及定量检验方法。实验算例表明，本文方法是一种有效的、鲁棒的非线性检验方法。

Surrogate data testing is an important statistical method to detect nonlinearity in time series and has been widely used.The choice of test statistics can bring important influence to the nonlinearity of time series.A method for testing nonlinearity is described based on the information theory－redundancy.We use the AAFT algorithm to produce surrogate data and using redundancy as test statistics.The evaluation of redundancy statistics for univariate and multivariate is  described respectively.The result of numerical experiments confirms our approach is an effective and robust nonlinearity detecting method.