XDGMM: eXtreme Deconvolution Gaussian Mixture Modeling
Abstract
XDGMM uses Gaussian mixtures to do density estimation of noisy, heterogenous, and incomplete data using extreme deconvolution (XD) algorithms which is compatible with the scikit-learn machine learning methods. It implements both the astroML and Bovy et al. (2011) algorithms, and extends the BaseEstimator class from scikit-learn so that cross-validation methods work. It allows the user to produce a conditioned model if values of some parameters are known.
- Publication:
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Astrophysics Source Code Library
- Pub Date:
- August 2017
- Bibcode:
- 2017ascl.soft08026H
- Keywords:
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- Software