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: 0.1.5
Depends: R (≥ 3.3.0)
Imports: methods, Rcpp (≥ 0.12.7)
LinkingTo: Rcpp
Suggests: testthat (≥ 1.0.2), knitr, rmarkdown
Published: 2016-11-22
Author: Dean Bodenham
Maintainer: Dean Bodenham <deanbodenhambsse at gmail.com>
License: GPL-2 | GPL-3
NeedsCompilation: yes
CRAN checks: ffstream results

Downloads:

Reference manual: ffstream.pdf
Vignettes: ffstream_0.1.4
Package source: ffstream_0.1.5.tar.gz
Windows binaries: r-devel: ffstream_0.1.5.zip, r-release: ffstream_0.1.5.zip, r-oldrel: ffstream_0.1.5.zip
OS X El Capitan binaries: r-release: ffstream_0.1.5.tgz
OS X Mavericks binaries: r-oldrel: ffstream_0.1.5.tgz
Old sources: ffstream archive

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