Returns critical values for the partial cross-quantilogram, based on the stationary bootstrap.
crossq.partial.sb(DATA, vecA, k, gamma, Bsize, sigLev)
The boostrap critical values
The original data matrix
A pair of two probability values at which sample quantiles are estimated
A lag order
A parameter for the stationary bootstrap
The number of repetition of bootstrap
The statistical significance level
Heejoon Han, Oliver Linton, Tatsushi Oka and Yoon-Jae Whang
This function generates critical values for for the partial cross-quantilogram, using the stationary bootstrap in Politis and Romano (1994).
Politis, Dimitris N., and Joseph P. Romano. "The stationary bootstrap." Journal of the American Statistical Association 89.428 (1994): 1303-1313.