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xLLiM  

High Dimensional Locally-Linear Mapping
View on CRAN: Click here


Download and install xLLiM package within the R console
Install from CRAN:
install.packages("xLLiM")

Install from Github:
library("remotes")
install_github("cran/xLLiM")

Install by package version:
library("remotes")
install_version("xLLiM", "2.3")



Attach the package and use:
library("xLLiM")
Maintained by
Emeline Perthame
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-12-05
Latest Update: 2023-10-27
Description:
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).
How to cite:
Emeline Perthame (2016). xLLiM: High Dimensional Locally-Linear Mapping. R package version 2.3, https://cran.r-project.org/web/packages/xLLiM. Accessed 15 Sep. 2026.
Previous versions and publish date:
(2026-07-09 06:56), 1.0 (2016-12-05 22:56), 2.0 (2017-05-16 16:46), 2.1 (2017-05-23 12:43), 2.2.1 (2023-09-11 17:50), 2.2 (2021-01-04 20:30), 2.3 (2023-10-27 12:10)
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Complete documentation for xLLiM
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