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-4.5)SAM_1.1.3.zip(r-4.4)SAM_1.1.3.zip(r-4.3)
SAM_1.1.3.tgz(r-4.4-x86_64)SAM_1.1.3.tgz(r-4.4-arm64)SAM_1.1.3.tgz(r-4.3-x86_64)SAM_1.1.3.tgz(r-4.3-arm64)
SAM_1.1.3.tar.gz(r-4.5-noble)SAM_1.1.3.tar.gz(r-4.4-noble)
SAM_1.1.3.tgz(r-4.4-emscripten)SAM_1.1.3.tgz(r-4.3-emscripten)
SAM.pdf |SAM.html
SAM/json (API)

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

Peer review:

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

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

On CRAN:

5.86 score 6 stars 4 packages 20 scripts 345 downloads 4.6k mentions 4 exports 2 dependencies

Last updated 3 years agofrom:9a0403b742. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 07 2024
R-4.5-win-x86_64NOTENov 07 2024
R-4.5-linux-x86_64NOTENov 07 2024
R-4.4-win-x86_64NOTENov 07 2024
R-4.4-mac-x86_64NOTENov 07 2024
R-4.4-mac-aarch64NOTENov 07 2024
R-4.3-win-x86_64NOTENov 07 2024
R-4.3-mac-x86_64NOTENov 07 2024
R-4.3-mac-aarch64NOTENov 07 2024

Exports:samELsamHLsamLLsamQL

Dependencies:RcppRcppEigen