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DeCAFS (version 3.2.3)

Detecting Changes in Autocorrelated and Fluctuating Signals

Description

Detect abrupt changes in time series with local fluctuations as a random walk process and autocorrelated noise as an AR(1) process. See Romano, G., Rigaill, G., Runge, V., Fearnhead, P. (2021) .

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Version

Install

install.packages('DeCAFS')

Monthly Downloads

181

Version

3.2.3

License

GPL (>= 2)

Maintainer

Gaetano Romano

Last Published

April 9th, 2021

Functions in DeCAFS (3.2.3)

scenarioGenerator

Generate a piecewise constant signal of a given length

evalEtaNu

RW and AR(1) variance estimations with fixed AR(1) parameter

dataSinusoidal

Generating data from a sinusoidal model with changes

DeCAFS

Main DeCAFS algorithm for detecting abrupt changes

oilWell

Rock structure data from an oil well

plot.DeCAFSout

DeCAFS Plotting

estimVar

Variance estimation for diff k operators

bestParameters

estimateParameters

Estimate parameter in the Random Walk Autoregressive model

cost

L2 error estimation

dataRWAR

Generate a Random Walk + AR realization