Bayesian Changepoint Detection

Methods to get the probability of a changepoint in a time series. Both online and offline methods are available. Read the following papers to really understand the methods:

[1] Paul Fearnhead, Exact and Efficient Bayesian Inference for Multiple
Changepoint problems, Statistics and computing 16.2 (2006), pp. 203--213

[2] Ryan P. Adams, David J.C. MacKay, Bayesian Online Changepoint Detection,
arXiv 0710.3742 (2007)

[3] Xuan Xiang, Kevin Murphy, Modeling Changing Dependency Structure in
Multivariate Time Series, ICML (2007), pp. 1055--1062

To see it in action have a look at the example notebook.

To install:

# Enter a directory of your choice, activate your python virtual environment.
git clone https://github.com/hildensia/bayesian_changepoint_detection.git
cd bayesian_changepoint_detection
pip install .
# Now can use bayesian_changepoint_detection in python.

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Or using pip - older version of this package, that doesn't work with python3:

pip install bayesian-changepoint-detection