dcbs.thr: Bootstrapping for threshold selection in DCBS algorithm

In hdbinseg: Change-Point Analysis of High-Dimensional Time Series via Binary Segmentation

Bootstrapping for threshold selection in DCBS algorithm

Description

Generate thresholds for DCBS algorithm via bootstrapping

Usage

dcbs.thr(
  z,
  interval = c(1, dim(z)[2]),
  phi = 0.5,
  cp.type = 1,
  do.clean.cp = FALSE,
  temporal = TRUE,
  scales = NULL,
  diag = FALSE,
  sgn = NULL,
  B = 1000,
  q = 0.01,
  do.parallel = 4
)

Arguments

z	input data matrix, with each row representing the component time series
interval	a vector of two containing the start and the end points of the interval from which the bootstrap test statistics are to be calculated
phi, cp.type, temporal, scales, diag, B, q, do.parallel	see dcbs.alg
do.clean.cp	if do.clean.cp = TRUE pre-change point cleaning is performed
sgn	if diag = FALSE, wavelet transformations of the cross-covariances are computed with the matching signs

Value

a numeric value for the threshold

hdbinseg documentation built on Aug. 17, 2023, 5:06 p.m.