Package: SAM 1.1.3

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.

Authors:Haoming Jiang, Yukun Ma, Han Liu, Kathryn Roeder, Xingguo Li, and Tuo Zhao

SAM_1.1.3.tar.gz
SAM_1.1.3.zip(r-4.7)SAM_1.1.3.zip(r-4.6)SAM_1.1.3.zip(r-4.5)
SAM_1.1.3.tgz(r-4.6-x86_64)SAM_1.1.3.tgz(r-4.6-arm64)SAM_1.1.3.tgz(r-4.5-x86_64)SAM_1.1.3.tgz(r-4.5-arm64)
SAM_1.1.3.tar.gz(r-4.7-arm64)SAM_1.1.3.tar.gz(r-4.7-x86_64)SAM_1.1.3.tar.gz(r-4.6-arm64)SAM_1.1.3.tar.gz(r-4.6-x86_64)
SAM_1.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
SAM/json (API)

# Install 'SAM' in R:
install.packages('SAM', repos = c('https://hmjianggatech.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/hmjianggatech/sam/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

cppopenmp

6.14 score 8 stars 4 packages 29 scripts 694 downloads 4.6k mentions 4 exports 2 dependencies

Last updated from:9a0403b742. Checks:11 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE119
linux-devel-x86_64NOTE137
source / vignettesOK147
linux-release-arm64NOTE135
linux-release-x86_64NOTE129
macos-release-arm64NOTE179
macos-release-x86_64NOTE318
macos-oldrel-arm64NOTE184
macos-oldrel-x86_64NOTE286
windows-develNOTE166
windows-releaseNOTE127
windows-oldrelNOTE132
wasm-releaseOK117

Exports:samELsamHLsamLLsamQL

Dependencies:RcppRcppEigen