breakfast (version 2.5)

Methods for Fast Multiple Change-Point/Break-Point Detection and Estimation

Description

A developing software suite for multiple change-point and change-point-type feature detection/estimation (data segmentation) in data sequences.

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Version

Install

install.packages('breakfast')

Monthly Downloads

312

Version

2.5

License

GPL-2

Maintainer

Yining Chen

Last Published

September 23rd, 2024

Functions in breakfast (2.5)

sol.wbs2

Solution path generation via the Wild Binary Segmentation 2 method

print.cptmodel

Change-points estimated by solution path generation + model selection methods

sol.idetect

Solution path generation via the Isolate-Detect method

sol.wcm

Solution path generation via the Wild Contrast Maximisation method

sol.wbs

Solution path generation via the Wild Binary Segmentation method

sol.tguh

Solution path generation via the Tail-Greedy Unbalanced Haar method

model.gsa

Estimating change-points in the piecewise-constant mean of a noisy data sequence with auto-regressive noise via gappy Schwarz algorithm

model.thresh

Estimating change-points in the piecewise-constant or piecewise-linear mean of a noisy data sequence via thresholding

print.breakfast.cpts

Change-points estimated by the "breakfast" routine

model.fixednum

Estimate the location of change-points when the number of them is fixed

model.lp

Estimating change-points in the piecewise-constant mean of a noisy data sequence via the localised pruning

plot.breakfast.cpts

Change-points estimated by the "breakfast" routine

breakfast

Methods for fast detection of multiple change-points

model.sdll

Estimating change-points in the piecewise-constant or piecewise-linear mean of a noisy data sequence via the Steepest Drop to Low Levels method

model.ic

Estimating change-points or change-point-type features in the mean of a noisy data sequence via the strengthened Schwarz information criterion

breakfast-package

Breakfast: Methods for Fast Multiple Change-point Detection and Estimation

sol.idetect_seq

Solution path generation using the sequential approach of the Isolate-Detect method

sol.not

Solution path generation via the Narrowest-Over-Threshold method