SAM: Sparse Additive Modelling

Computationally efficient tools for high dimensional predictive modeling (regression and classification). SAM is short for sparse additive modeling, and adopts the computationally efficient basis spline technique. We solve the optimization problems by various computational algorithms including the block coordinate descent algorithm, fast iterative soft-thresholding algorithm, and newton method. The computation is further accelerated by warm-start and active-set tricks.

Version: 1.1.3
Depends: R (≥ 2.14), splines
Imports: Rcpp
LinkingTo: Rcpp, RcppEigen
Published: 2021-07-01
DOI: 10.32614/CRAN.package.SAM
Author: Haoming Jiang, Yukun Ma, Han Liu, Kathryn Roeder, Xingguo Li, and Tuo Zhao
Maintainer: Haoming Jiang <jianghm.ustc at>
License: GPL-2
NeedsCompilation: yes
CRAN checks: SAM results


Reference manual: SAM.pdf


Package source: SAM_1.1.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): SAM_1.1.3.tgz, r-oldrel (arm64): SAM_1.1.3.tgz, r-release (x86_64): SAM_1.1.3.tgz, r-oldrel (x86_64): SAM_1.1.3.tgz
Old sources: SAM archive

Reverse dependencies:

Reverse imports: DLL, GSelection, pgraph, varEst


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