Package: ffstream
Title: Forgetting Factor Methods for Change Detection in Streaming Data
Version: 0.1.5
Author: Dean Bodenham
Maintainer: Dean Bodenham <deanbodenhambsse@gmail.com>
Description: 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.
Depends: R (>= 3.3.0)
License: GPL-2 | GPL-3
LazyData: true
LinkingTo: Rcpp
Imports: methods, Rcpp (>= 0.12.7)
Suggests: testthat (>= 1.0.2), knitr, rmarkdown
RoxygenNote: 5.0.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2016-11-22 16:36:49 UTC; dean
Repository: CRAN
Date/Publication: 2016-11-22 18:23:27
Built: R 3.3.2; x86_64-apple-darwin13.4.0; 2016-11-23 13:56:00 UTC; unix
Archs: ffstream.so.dSYM
