The Multiple Filter Test for Change Point Detection R package MFT version 3.1 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 (2020) A multi-scale approach for testing and detecting peaks in time series <doi:10.1080/02331888.2020.1823980>. Software Michael Messer <michaelmessermath@gmail.com> Comprehensive R Archive Network (CRAN) Michael Messer [aut, cre], Stefan Albert [aut], Solveig Plomer [aut], Gaby Schneider [aut] GPL-3 2026-09-16 application/tgz https://CRAN.R-project.org/package=MFT doi:10.32614/CRAN.package.MFT