In this work we present a nonparametric test to detect nonlinearity in time series. The test is based on permutation methods and essentially it is a distributional comparison between two sub-populations. We evaluate the significance nominal level and the power of tests by simulation considering differen t linear and nonlinear models. As benchmarking we use some well known nonlinearity tests.
Nonparametric strategies applied to time series analysis
PIZZI, Claudio;PARPINEL, Francesca
2006-01-01
Abstract
In this work we present a nonparametric test to detect nonlinearity in time series. The test is based on permutation methods and essentially it is a distributional comparison between two sub-populations. We evaluate the significance nominal level and the power of tests by simulation considering differen t linear and nonlinear models. As benchmarking we use some well known nonlinearity tests.File in questo prodotto:
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