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.


Reference manual

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0.1.5 by Dean Bodenham, 3 months ago

Browse source code at

Authors: Dean Bodenham

Documentation:   PDF Manual  

GPL-2 | GPL-3 license

Imports methods, Rcpp

Suggests testthat, knitr, rmarkdown

Linking to Rcpp

See at CRAN