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/s11222-014-9461-5>) based on Gaussian mixtures and a robust version of GLLiM, named SLLiM (see Perthame et al (2016) <doi:10.1016/j.jmva.2017.09.009>) based on a mixture of Generalized Student distributions. The methods also include BLLiM (see Devijver et al (2017) <doi:10.48550/arXiv.1701.07899>) which is an extension of GLLiM with a sparse block diagonal structure for large covariance matrices (particularly interesting for transcriptomic data).
| Version: | 2.3 |
| Imports: | MASS,abind,corpcor,Matrix,igraph,capushe,glmnet,randomForest,e1071,mda,progress,mixOmics |
| Suggests: | shock |
| Published: | 2023-10-27 |
| DOI: | 10.32614/CRAN.package.xLLiM |
| Author: | Emeline Perthame (emeline.perthame@inria.fr), Florence Forbes (florence.forbes@inria.fr), Antoine Deleforge (antoine.deleforge@inria.fr), Emilie Devijver (emilie.devijver@kuleuven.be), Melina Gallopin (melina.gallopin@u-psud.fr) |
| Maintainer: | Emeline Perthame <emeline.perthame at pasteur.fr> |
| License: | GPL-2 |GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | xLLiM results |