clean.cp: Removing change-points in the mean

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

Removing change-points in the mean

Description

(Over-)estimate and remove change-points in the mean for scale estimation and bootstrapping

Usage

clean.cp(z, type = c("dcbs", "sbs"), phi = 0.5, trim = NULL, height = NULL)

Arguments

z	input data matrix, with each row representing the component time series
type	if type = 'dcbs', a binary tree of given height is grown using DCBS algorithm without thresholding, if type = 'sbs', the binary trees is grown using the SBS algorithm with thresholds chosen small
phi, trim, height	see dcbs.alg

Value

a list containing

x	z with potential change-points in the mean removed
z	mat object of an S3 bin.tree object

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