ffstream (0.1.6)

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Forgetting Factor Methods for Change Detection in Streaming Data.


An implementation of the adaptive forgetting factor scheme described in Bodenham and Adams (2016) 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.

Maintainer: Dean Bodenham
Author(s): Dean Bodenham

License: GPL-2 | GPL-3

Uses: Rcpp, testthat, knitr, rmarkdown

Released over 1 year ago.

2 previous versions



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