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
DESCRIPTION
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

6.20 score 8 stars 4 packages 33 scripts 762 downloads 4.6k mentions 4 exports 2 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE145
linux-devel-x86_64NOTE120
source / vignettesOK149
linux-release-arm64NOTE120
linux-release-x86_64NOTE140
macos-release-arm64NOTE123
macos-release-x86_64NOTE211
macos-oldrel-arm64NOTE114
macos-oldrel-x86_64NOTE381
windows-develNOTE137
windows-releaseNOTE153
windows-oldrelNOTE124
wasm-releaseOK105

Exports:samELsamHLsamLLsamQL

Dependencies:RcppRcppEigen