Package: ffstream
Title: Forgetting Factor Methods for Change Detection in Streaming Data
Version: 0.1.7.2
Date: 2023-05-25
Author: Dean Bodenham 
Maintainer: Dean Bodenham <deanbodenhampkgs@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 cumulative sum ('CUSUM') and exponentially weighted moving average ('EWMA') methods, are included.
Depends: R (>= 4.1.0), Rcpp (>= 1.0.0)
License: GPL-2 | GPL-3
LinkingTo: Rcpp
Imports: methods
Suggests: testthat (>= 2.0.0), knitr, rmarkdown
Encoding: UTF-8
RoxygenNote: 7.2.3
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2023-05-30 09:46:35 UTC; dean
Repository: CRAN
Date/Publication: 2023-05-30 10:20:02 UTC
Built: R 4.3.0; x86_64-apple-darwin20; 2023-05-30 10:37:44 UTC; unix
Archs: ffstream.so.dSYM
