test_op_bp_bootstrap

docblock

test_op_bp_bootstrap(data, n_boot, w; chart_choice, m=3, alpha=0.05,
  ljung_box=false, block_size=1)

Compute a bootstrap Box-Pierce type hypothesis test for ordinal patterns and return an OPBPTestResultBoot with the bootstrap critical value, p-value, and reject decision.

Unlike test_op_bp, this does not rely on tabulated critical values and therefore works for any chart, any pattern length m, any maximal delay w and any significance level alpha.

data: the time series.
n_boot: number of bootstrap replications.
w: maximal delay; the individual statistics for delays 1:w are aggregated.
chart_choice: one of Shannon(), ShannonExtropy(), DistanceToWhiteNoise(), UpDownBalance(), Persistence(), RotationalAsymmetry(), UpDownScaling(). For Shannon and ShannonExtropy, the logarithm base must be larger than 1. The statistic does not depend on it.
m::Int=3: length of the ordinal patterns.
alpha: significance level (default 0.05).
ljung_box::Bool=false: if true, use Ljung-Box (BL) weights.
block_size: set > 1 for a block bootstrap that preserves serial dependencies.