Fast inference over mean and covariance parameters for Generalised Linear Mixed Models. It implements the mathematical tricks of FaST-LMM for the special case of Linear Mixed Models with a linear covariance matrix and provides an interface to perform inference over millions of covariates in seconds. (Refer to FastScanner for details.) The Generalised Linear Mixed Model inference is implemented via Expectation Propagation and also makes use of several mathematical tricks to handle large data sets with thousands of samples and millions of covariates. (Refer to GLMMExpFam and FastScanner for details.)
The recommended way of installing it is via conda
conda install -c conda-forge glimix-core
An alternative way would be via pip
pip install glimix-core
After installation, you can test it
python -c "import glimix_core; glimix_core.test()"
as long as you have pytest.
This project is licensed under the MIT License - see the License file file for details.