ffstream: Forgetting Factor Methods for Change Detection in Streaming Data

An implementation of the adaptive forgetting factor scheme described in Bodenham and Adams (2016) <doi:10.1007/s11222-016-9684-8> which adaptively estimates the mean and variance of a stream in order to detect multiple changepoints in streaming data. The implementation is in C++ and uses Rcpp. Additionally, implementations of the fixed forgetting factor scheme from the same paper, as well as the classic CUSUM and EWMA methods, are included.

Version: 0.1.6
Depends: R (≥ 3.5.0), Rcpp (≥ 0.12.16)
Imports: methods
LinkingTo: Rcpp
Suggests: testthat (≥ 2.0.0), knitr, rmarkdown
Published: 2018-05-14
Author: Dean Bodenham
Maintainer: Dean Bodenham <deanbodenhampkgs at gmail.com>
License: GPL-2 | GPL-3
URL: http://www.deanbodenham.com/ffstream
NeedsCompilation: yes
Materials: NEWS
CRAN checks: ffstream results

Downloads:

Reference manual: ffstream.pdf
Vignettes: ffstream_0.1.6
Package source: ffstream_0.1.6.tar.gz
Windows binaries: r-devel: ffstream_0.1.6.zip, r-devel-gcc8: ffstream_0.1.6.zip, r-release: ffstream_0.1.6.zip, r-oldrel: ffstream_0.1.6.zip
OS X binaries: r-release: ffstream_0.1.6.tgz, r-oldrel: ffstream_0.1.6.tgz
Old sources: ffstream archive

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