Package: MFT
Type: Package
Title: The Multiple Filter Test for Change Point Detection
Version: 2.0
Date: 2019-03-11
Author: Michael Messer, Stefan Albert, Solveig Plomer, Gaby Schneider
Maintainer: Michael Messer <messer@math.uni-frankfurt.de>
Description: Provides statistical tests and algorithms for the detection of change points in time series and point processes - particularly for changes in the mean in time series and for changes in the rate and in the variance in point processes. References - Michael Messer, Marietta Kirchner, Julia Schiemann, Jochen Roeper, Ralph Neininger and Gaby Schneider (2014), A multiple filter test for the detection of rate changes in renewal processes with varying variance <doi:10.1214/14-AOAS782>. Stefan Albert, Michael Messer, Julia Schiemann, Jochen Roeper, Gaby Schneider (2017), Multi-scale detection of variance changes in renewal processes in the presence of rate change points <doi:10.1111/jtsa.12254>. Michael Messer, Kaue M. Costa, Jochen Roeper and Gaby Schneider (2017), Multi-scale detection of rate changes in spike trains with weak dependencies <doi:10.1007/s10827-016-0635-3>. Michael Messer, Stefan Albert and Gaby Schneider (2018), The multiple filter test for change point detection in time series <doi:10.1007/s00184-018-0672-1>. Michael Messer, Hendrik Backhaus, Albrecht Stroh and Gaby Schneider (2019+) Peak detection in time series.  
License: GPL-3
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-11 18:08:51 UTC; messer
Repository: CRAN
Date/Publication: 2019-03-11 20:42:55 UTC
Built: R 4.6.0; ; 2026-04-25 20:21:37 UTC; unix
