ffstream: Forgetting Factor Methods for Change Detection in Streaming Data
Version 0.1.5

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.

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Package details

AuthorDean Bodenham
Date of publication2016-11-22 18:23:27
MaintainerDean Bodenham <[email protected]>
LicenseGPL-2 | GPL-3
Package repositoryView on CRAN
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ffstream documentation built on May 29, 2017, 10:33 p.m.