Granger causal inference is a contentious but widespread method used in fields ranging from economics to neuroscience.
Change Point Detection With Conceptors
For the at most one change point problem, we propose the use of a conceptor matrix to learn the characteristic dynamics of a specified training window in a time series.
GitHub Link
The GitHub link is https://github.com/noahgade/changepointdetectionwithconceptorsIntroduce
Title GitHub Repository for Change Point Detection Using Conceptors Summary The GitHub repository "ChangePointDetectionWithConceptors" by user noahgade focuses on Change Point Detection using Conceptors. It offers the R-package "conceptorCP" for implementing the methods detailed in the associated article. The repository includes simulated data for method evaluation, code to generate results and figures mentioned in the paper, as well as datasets and code for the application study in Section 5. For the at most one change point problem, we propose the use of a conceptor matrix to learn the characteristic dynamics of a specified training window in a time series.Content
Repository includes:- R-package conceptorCP (link to GitHub page) containing code to perform the methods described in the article. (GNU zipped tar file)
- Simulated data used to assess performance of change point methods. (.RData files)
- Code used to generate results and figures discussed in paper. (.R file)
- Data set used in application study Section 5. (.RData file)
- Code used to assess the methods in the application study. (.R file)
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