Surrogate Data Testing

First published: 2000

Brief summary

Review on surrogate data methods for nonlinear time series.

Article

Surrogate Data Testing is covered by the linked source. Review on surrogate data methods for nonlinear time series.

The material from Physics Reports describes a method for detecting, decomposing, testing or reproducing structure in time-series data.

Reliable use requires attention to sampling, trend, missing values, noise, boundaries, parameter choices and multiple testing. Sensitivity checks help assess stability.

No method can confirm a genuine cycle from an attractive graph or isolated peak alone. Significance requires an appropriate null model and documented preprocessing.

Source details and credits

• Source / publisher: Physics Reports
• Source type: Review
• URL type: WWW
• Credits: Physics Reports
• URL: https://doi.org/10.1016/S0370-1573(99)00091-7