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.
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.