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SAM  

Sparse Additive Modelling
View on CRAN: Click here


Download and install SAM package within the R console
Install from CRAN:
install.packages("SAM")

Install from Github:
library("remotes")
install_github("cran/SAM")

Install by package version:
library("remotes")
install_version("SAM", "1.1.3")



Attach the package and use:
library("SAM")
Maintained by
Haoming Jiang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-10-15
Latest Update: 2021-07-01
Description:
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.
How to cite:
Haoming Jiang (2012). SAM: Sparse Additive Modelling. R package version 1.1.3, https://cran.r-project.org/web/packages/SAM. Accessed 26 Aug. 2026.
Previous versions and publish date:
(2026-07-09 08:24), 1.0.2 (2012-10-15 18:25), 1.0.3 (2013-04-02 00:46), 1.0.4 (2013-09-18 17:08), 1.0.5 (2014-02-12 09:34), 1.1.0 (2019-02-18 17:10), 1.1.1 (2019-03-12 00:42), 1.1.2.1 (2019-07-02 09:21), 1.1.2 (2019-04-07 20:32), 1.1.3 (2021-07-01 09:10), 1.2 (2026-02-19 11:50)
Other packages that cited SAM R package
View SAM citation profile
Other R packages that SAM depends, imports, suggests or enhances
Complete documentation for SAM
Functions, R codes and Examples using the SAM R package
Some associated functions: SAM-package . plot.samEL . plot.samHL . plot.samLL . plot.samQL . predict.samEL . predict.samHL . predict.samLL . predict.samQL . print.samEL . print.samHL . print.samLL . print.samQL . samEL . samHL . samLL . samQL . 
Some associated R codes: SAM-package.R . samEL.R . samHL.R . samLL.R . samQL.R .  Full SAM package functions and examples
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