File Exchange

image thumbnail

Change-point detection using the conditional entropy of ordinal patterns

version 1.2.0.0 (9.46 KB) by Anton
Detecting change-point using the ordinal structure of a time series

7 Downloads

Updated 14 May 2018

View Version History

View License

FindAllOrdinalCP.m - detects structural change-points by using CEofOP statistic [UK15] and returns positions of all detected change-points. Ordinal patterns are computed using the fast algorithm presented in [UK13].
Input parameters of the change-point detection algorithm include:
- falseAlarmRate - assigned probability of a false alarm (erroneously detected change-point in a stationary signal). falseAlarmRate = 0.05 is acceptable in many cases.
- minCPdist - minimal distance between change-points (minimal expected length of a stationary segment). For example in EEG time series one may expect stationary segments to be at least of 1-2 seconds, which means that
minCPdist = samplingRate;
or
minCPdist = 2*samplingRate;
could be used
- order - order of ordinal patterns to be used for ordinal change-point detection (please, see [UK13, UK15] for details). Order values of 2 or 3 are recommended. If you expect that the stationary segments in the time series are longer than 20 but shorter than 100 (minCPdist > 20, but minCPdist < 100), please use you order = 2. If you expect that all stationary segments in the time series are longer than 100 (minCPdist >= 100), please use you order = 3 .
ChangePointExample - example of using FindAllOrdinalCP.
GenerateARWithChange.m, GenerateLogisticWithChange.m - generate examples of time series with structural change-points (see [UK15]).
[UK15] Unakafov, A.M. and Keller, K., 2015. Change-point detection using the conditional entropy of ordinal patterns. arXiv preprint arXiv:1510.01457.
[UK13] Unakafova, V.A., Keller, K., 2013. Efficiently measuring complexity on the basis of real-world Data. Entropy, 15(10), 4392-4415.

Cite As

Anton (2020). Change-point detection using the conditional entropy of ordinal patterns (https://www.mathworks.com/matlabcentral/fileexchange/62944-change-point-detection-using-the-conditional-entropy-of-ordinal-patterns), MATLAB Central File Exchange. Retrieved .

Comments and Ratings (4)

fei wang

Dragos Popa

Anton

Hello Enliang Guo,
thank you for your comment, this issue is resolved in the new version

Enliang Guo

when I run ChangePointExample.m
Error using FindAllOrdinalCP> CalcOrdinalTimeSeries
Too many input parameters.
why?

MATLAB Release Compatibility
Created with R2013b
Compatible with any release
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!