A package for dimensionality reduction of multivariate extremes using the idea of PCA to obtain a resonable compact description of the data.
- Transform a dataset to standard margins to use well known ideas from extreme value theory
- Perform a dimensionality reduction of a dataset to a fixed number of encoding variables. For further information about the theory of this consider looking at the references.
- Evaluate the quality of this reconstruction.
- Transform the data back to the distribution of the original dataset.
For a better feeling of what this algorithm does, please consider looking at the following links providing example data analyses and simulation studies
- Related GitHub repository: https://github.com/FelixRb96/maxstablePCA_examples
- TODO: Rdocumentation, maybe some towardsdatascience blog or sth.
- A semi-group approach to Principal Component Analysis, Schlather M., Reinbott F., arxiv preprint, https://arxiv.org/pdf/2112.04026.pdf, 2021