Package: MFT 2.0

Michael Messer

MFT: The Multiple Filter Test for Change Point Detection

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.

Authors:Michael Messer, Stefan Albert, Solveig Plomer, Gaby Schneider

MFT_2.0.tar.gz
MFT_2.0.tar.gz(r-4.5-noble)MFT_2.0.tar.gz(r-4.4-noble)
MFT_2.0.tgz(r-4.4-emscripten)MFT_2.0.tgz(r-4.3-emscripten)
MFT.pdf |MFT.html✨
MFT/json (API)

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

6 exports 4.50 score 0 dependencies 44 mentions 9 scripts 130 downloads

Last updated 6 years agofrom:db17d0591c. Checks:OK: 2. Indexed: yes.

Exports:MFT.filterdataMFT.m_estMFT.meanMFT.peaksMFT.rateMFT.variance

Dependencies: