gemmr - Generative Modeling of Multivariate Relationships

gemmr calculates required sample sizes for Canonical Correlation Analysis (CCA) and Partial Least Squares (PLS). In addition, it can generate synthetic datasets for use with CCA and PLS, and provides functionality to run and examine CCA and PLS analyses. It also provides a Python wrapper for PMA, a sparse CCA implementation.

Dependencies

• numpy
• scipy
• pandas
• xarray
• netcdf4
• scikit-learn
• statsmodels
• joblib
• tqdm

Some functions have additional dependencies that need to be installed separately if they are used:

• holoviews
• rpy2

Installation

The easiest way to install gemmr is with pip:

pip install gemmr

Alternatively, to install and use the most current code:

git clone https://github.com/mdhelmer/gemmr.git
cd gemmr
python setup.py install

Documentation

Extensive documentation can be found here.

To generate the documentation from source, install gemmr as described above and make sure you also have the following dependencies installed:

• ipython
• matplotlib
• sphinx
• nbsphinx
• sphinx_rtd_theme and run (in the doc subfolder):

make html

and open doc/_build/html/index.html .

Citation

If you're using gemmr in a publication, please cite TODO