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 gmail.com> License: GPL-2 NeedsCompilation: yes CRAN checks: SAM results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=SAM to link to this page.
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