xLLiM

Provides a tool for non linear mapping (non linear regression) using a mixture of regression model and an inverse regression strategy. The methods include the GLLiM model (see Deleforge et al (2015) ) based on Gaussian mixtures and a robust version of GLLiM, named SLLiM (see Perthame et al (2016) ) based on a mixture of Generalized Student distributions. The methods also include BLLiM (see Devijver et al (2017) ) which is an extension of GLLiM with a sparse block diagonal structure for large covariance matrices (particularly interesting for transcriptomic data).

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