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IDetect (version 0.1.0)

Isolate-Detect Methodology for Multiple Change-Point Detection

Description

Provides efficient implementation of the Isolate-Detect methodology for the consistent estimation of the number and location of multiple change-points in one-dimensional data sequences from the "deterministic + noise" model. For details on the Isolate-Detect methodology, please see Anastasiou and Fryzlewicz (2018) . Currently implemented scenarios are: piecewise-constant signal with Gaussian noise, piecewise-constant signal with heavy-tailed noise, continuous piecewise-linear signal with Gaussian noise, continuous piecewise-linear signal with heavy-tailed noise.

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Version

Install

install.packages('IDetect')

Monthly Downloads

166

Version

0.1.0

License

GPL-3

Maintainer

Andreas Anastasiou

Last Published

March 9th, 2018

Functions in IDetect (0.1.0)

ID

Multiple change-point detection in piecewise-constant or continuous, piecewise-linear signals using the Isolate-Detect methodology
IDetect

IDetect: Multiple generalised change-point detection using the Isolate-Detect methodology
resid_ID

Calculate the residuals related to the estimated signal
sol_path_cplm

The solution path for the case of continuous piecewise-linear signals
sol_path_pcm

The solution path for the case of piecewise-constant signals
s_e_points

Derives a subset of integers from a given set
ht_ID_pcm

Apply the Isolate-Detect methodology for multiple change-point detection in the mean of a vector with non Gaussian noise
cplm_ic

Multiple change-point detection in a continuous piecewise-linear signal via minimising an information criterion
normalise

Transform the noise to be closer to the Gaussian distribution
win_cplm_th

A windows-based approach for multiple change-point detection in a continuous, piecewise-linear signal via thresholding
win_pcm_th

A windows-based approach for multiple change-point detection in the mean via thresholding
cplm_th

Multiple change-point detection in a continuous, piecewise-linear signal via thresholding
est_signal

Estimate the signal
pcm_th

Multiple change-point detection in the mean via thresholding
pcm_ic

Multiple change-point detection in the mean via minimising an information criterion
ht_ID_cplm

Apply the Isolate-Detect methodology for multiple change-point detection in a continuous, piecewise-linear vector with non Gaussian noise
ID_cplm

Multiple change-point detection for a continuous, piecewise-linear signal using the Isolate-Detect methodology
ID_pcm

Multiple change-point detection in the mean of a vector using the Isolate-Detect methodology