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.
| 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 | 
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