pyhctsa.operations.nonlinearity.nlpe¶

pyhctsa.operations.nonlinearity.nlpe(y, de=3, tau=1, max_n=5000)¶

Normalized drop-one-out constant interpolation nonlinear prediction error.

Computes the nlpe for a time-delay embedded time series using Michael Small’s code, nlpe [1].

Modifications by Joshua B. Moore for incorporating into pyhctsa.

References

Parameters:¶

y : array-like¶

Input time series.

de : int¶

The embedding dimension. Default is 3.

tau : int or str, optional¶

The time-delay. Can be either an integer or 'ac' to use the first zero-crossing of the ACF, or 'mi' to use the first minimum of the automutual information function. Default is 1.

max_n : int, optional¶

The maximum length of the time series on which to compute the nlpe. Default is 5000.

Returns:¶

Measures of the mean error of the nonlinear predictor, and a set of measures on the correlation, Gaussianity, etc. of the residuals.

Return type:¶

dict