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) <DOI:10.1007/s1122201494615>) based on Gaussian mixtures and a robust version of GLLiM, named SLLiM (see Perthame et al (2016) <https://hal.archivesouvertes.fr/hal01347455>) based on a mixture of Generalized Student distributions. The methods also include BLLiM (see Devijver et al (2017) <https://arxiv.org/abs/1701.07899>) which is an extension of GLLiM with a sparse block diagonal structure for large covariance matrices (particularly interesting for transcriptomic data).
Package details 


Author  Emeline Perthame ([email protected]), Florence Forbes ([email protected]), Antoine Deleforge ([email protected]), Emilie Devijver ([email protected]), Melina Gallopin ([email protected]) 
Maintainer  Emeline Perthame <[email protected]> 
License  GPL (>= 2) 
Version  2.1 
Package repository  View on CRAN 
Installation 
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