RcppEigen back end for sparse least trimmed squares regression

Use RcppEigen to fit least trimmed squares regression models with an L1 penalty in order to obtain sparse models.


News

Changes in sparseLTSEigen version 0.2.0

+ Adapted C++ code to new version of package 'robustHD'.

Changes in sparseLTSEigen version 0.1.3

+ Bugfix in sparseLTS() in case of only one predictor variable.

Changes in sparseLTSEigen version 0.1.2

+ Redesign of how C++ back end is called from package 'robustHD'.

+ Adapted C++ code to new version of package 'robustHD'.

+ Bugfix in fastSparseLTS() for more stability of the results.

Changes in sparseLTSEigen version 0.1.1

+ Parallel computing is now available via OpenMP.

+ Adapted example to those of package robustHD.

Reference manual

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install.packages("sparseLTSEigen")

0.2.0 by Andreas Alfons, 5 years ago


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


Authors: Andreas Alfons [aut, cre]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp, RcppEigen

Depends on robustHD

Suggests mvtnorm

Linking to Rcpp, RcppEigen


See at CRAN