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On testing for nonlinearity in multivariate time series

机译:关于多元时间序列中的非线性测试

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This paper considers a multivariate extension of the test for neglected nonlinearity proposed by Tsay (1986) that uses principal components to overcome the problem of dimensionality that is common with tests of this type. Monte Carlo experiments reveal that the modified multivariate test provides a significant dimensional reduction without suffering from any systematic level distortion or power loss, and is more powerful than univariate nonlinearity tests.
机译:本文考虑了Tsay(1986)提出的针对被忽略的非线性检验的多元扩展,该检验使用主成分来克服此类检验中常见的尺寸问题。蒙特卡洛实验表明,改进的多元测试可显着减小尺寸,而不会遭受任何系统级的失真或功率损耗,并且比单变量非线性测试更强大。

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