Randomization test for nonlinearity using S-maps and surrogate data

test_nonlinearity tests for nonlinearity using S-maps by comparing improvements in forecast skill (delta rho and delta mae) between linear and nonlinear models with a null distribution from surrogate data.

test_nonlinearity(ts, method = "ebisuzaki", num_surr = 200,
  T_period = 1, E = 1, ...)

Arguments

ts	the original time series
method	which algorithm to use to generate surrogate data
num_surr	the number of null surrogates to generate
T_period	the period of seasonality for seasonal surrogates (ignored for other methods)
E	the embedding dimension for s_map
...	optional arguments to s_map

Value

A data.frame containing the following components:

delta_rho	the value of the delta rho statistic
delta_mae	the value of the delat mae statistic
num_surr	the size of the null distribution
delta_rho_p_value	the p-value for delta rho
delta_mae_p_value	the p-value for delta mae