mmer 1.0.1

MMER: Multivariate Mixed Effects Regression.

MMER - Multivariate Mixed Effects Regression

MMER is a Python package for multivariate mixed-effects regression. It uniquely features a modular fixed-effect component, supporting both parametric models and non-parametric machine learning regressors (e.g., neural networks, random forests, XGBoost). MMER handles multiple responses, grouping factors, and linear random effects structures [1].

Table of Contents

• Features and Installation
• User Guide
• License
• Contact
• References

Features and Installation

See the Documentation.

User Guide

The full documentation, including examples and the complete API reference, is available at mmer.readthedocs.io.

License

MMER is released under the MIT License.
See the LICENSE file for the full text.

Contact

For questions or assistance, please feelfree to contact:

S.M. Sajad Hussaini
📧 [e-mail]

Please include "MMER" in the subject line for a quicker response.

Support the Project

If you find this package useful, contributions to help maintain and improve it, are always appreciated.

References

Please cite the following references for any formal study:

[1] Primary Reference
A Multivariate Mixed-Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches
DOI: [To be added]
(Expected publication in the Journal of Earthquake Engineering and Structural Dynamics)

[2] MMER Package
MMER: Multivariate Mixed Effects Regression
DOI: https://doi.org/10.5281/zenodo.18068839