Package: DeCAFS 3.3.5

DeCAFS: Detecting Changes in Autocorrelated and Fluctuating Signals

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) <doi:10.1080/01621459.2021.1909598>.

Authors:Gaetano Romano [aut, cre], Guillem Rigaill [aut], Vincent Runge [aut], Paul Fearnhead [aut]

DeCAFS_3.3.5.tar.gz
DeCAFS_3.3.5.zip(r-4.7-x86_64)DeCAFS_3.3.5.zip(r-4.6-x86_64)DeCAFS_3.3.5.zip(r-4.5-x86_64)
DeCAFS_3.3.5.tgz(r-4.6-x86_64)DeCAFS_3.3.5.tgz(r-4.6-arm64)DeCAFS_3.3.5.tgz(r-4.5-x86_64)DeCAFS_3.3.5.tgz(r-4.5-arm64)
DeCAFS_3.3.5.tar.gz(r-4.7-arm64)DeCAFS_3.3.5.tar.gz(r-4.7-x86_64)DeCAFS_3.3.5.tar.gz(r-4.6-arm64)DeCAFS_3.3.5.tar.gz(r-4.6-x86_64)
DeCAFS_3.3.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
DeCAFS/json (API)

# Install 'DeCAFS' in R:

install.packages('DeCAFS', repos = c('https://gtromano.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/gtromano/decafs/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

oilWell - Rock structure data from an oil well

On CRAN:

change-detection changepoint-detection time-series-analysis cpp

3.18 score 3 stars 3 scripts 349 downloads 11 exports 20 dependencies

Last updated from:9d01446d4a. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	146
linux-devel-x86_64	OK	130
source / vignettes	OK	192
linux-release-arm64	OK	130
linux-release-x86_64	OK	123
macos-release-arm64	OK	131
macos-release-x86_64	OK	249
macos-oldrel-arm64	OK	91
macos-oldrel-x86_64	OK	172
windows-devel	OK	129
windows-release	OK	136
windows-oldrel	OK	114
wasm-release	OK	135

Exports:bestParameters cost dataRWAR dataSinusoidal DeCAFS estimateParameters estimVar evalEtaNu guidedModelSelection plot.DeCAFSout scenarioGenerator

Dependencies:cli cpp11 DEoptimR farver ggplot2 glue gtable isoband labeling lifecycle R6 RColorBrewer Rcpp rlang robustbase S7 scales vctrs viridisLite withr

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
bestParameters	bestParameters
L2 error estimation	cost
Generate a Random Walk + AR realization	dataRWAR
Generating data from a sinusoidal model with changes	dataSinusoidal
Main DeCAFS algorithm for detecting abrupt changes	DeCAFS
Estimate parameter in the Random Walk Autoregressive model	estimateParameters
Variance estimation for diff k operators	estimVar
RW and AR(1) variance estimations with fixed AR(1) parameter	evalEtaNu
Guided Model Selection	guidedModelSelection
Rock structure data from an oil well	oilWell
DeCAFS Plotting	plot.DeCAFSout
Generate a piecewise constant signal of a given length	scenarioGenerator