xLLiM: High Dimensional Locally-Linear Mapping
Version 2.1

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).

Package details

AuthorEmeline Perthame ([email protected]), Florence Forbes ([email protected]), Antoine Deleforge ([email protected]), Emilie Devijver ([email protected]), Melina Gallopin ([email protected])
Date of publication2017-05-23 10:43:05 UTC
MaintainerEmeline Perthame <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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xLLiM documentation built on May 30, 2017, 1:26 a.m.