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 |
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:
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