| nonlinearity {tsfeatures} | R Documentation |
Nonlinearity coefficient
Description
Computes a nonlinearity statistic based on Lee, White & Granger's nonlinearity test of a time series.
The statistic is 10X^2/T where X^2 is the Chi-squared statistic from Lee, White and Granger,
and T is the length of the time series. This takes large values
when the series is nonlinear, and values around 0 when the series is linear.
Usage
nonlinearity(x)
Arguments
x |
a univariate time series |
Value
A numeric value.
Author(s)
Yanfei Kang and Rob J Hyndman
References
Lee, T. H., White, H., & Granger, C. W. (1993). Testing for neglected nonlinearity in time series models: A comparison of neural network methods and alternative tests. Journal of Econometrics, 56(3), 269-290.
Teräsvirta, T., Lin, C.-F., & Granger, C. W. J. (1993). Power of the neural network linearity test. Journal of Time Series Analysis, 14(2), 209–220.
Examples
nonlinearity(lynx)