Multiple Change-Point Detection and Segmentation

Documentation for package ‘breakfast’ version 1.0.0

breakfast-package	breakfast: Multiple change-point detection and segmentation for data sequences
breakfast	breakfast: Multiple change-point detection and segmentation for data sequences
hybrid.cpt	Multiple change-point detection in the mean of a vector using a hybrid between the TGUH and Adaptive WBS methods.
segment.mean	Multiple change-point detection in the mean of a vector
tguh.cpt	Multiple change-point detection in the mean of a vector using the TGUH method
tguh.decomp	The Tail-Greedy Unbalanced Haar decomposition of a vector
tguh.denoise	Noise removal from Tail-Greedy Unbalanced Haar coefficients via connected thresholding
tguh.reconstr	The inverse Tail-Greedy Unbalanced Haar transformation
wbs.bic.cpt	Multiple change-point detection in the mean of a vector using the WBS method, with the number of change-points chosen by BIC
wbs.cpt	Multiple change-point detection in the mean of a vector using the (Adaptive) WBS method.
wbs.K.cpt	Detecting exactly 'K' change-points in the mean of a vector using the Adaptive WBS method
wbs.thresh.cpt	Multiple change-point detection in the mean of a vector using the (Adaptive) WBS method, with the number of change-points chosen by thresholding