High Dimensional Locally-Linear Mapping

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) < https://hal.archives-ouvertes.fr/hal-01347455>) 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).


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Reference manual

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install.packages("xLLiM")

2.1 by Emeline Perthame, 2 years ago


Browse source code at https://github.com/cran/xLLiM


Authors: Emeline Perthame ([email protected]) , Florence Forbes ([email protected]) , Antoine Deleforge ([email protected]) , Emilie Devijver ([email protected]) , Melina Gallopin ([email protected])


Documentation:   PDF Manual  


GPL (>= 2) license


Imports MASS, abind, corpcor, Matrix, igraph, capushe

Suggests shock


See at CRAN