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.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


1.1.2 by Haoming Jiang, 2 months ago

Browse source code at

Authors: Haoming Jiang , Yukun Ma , Han Liu , Kathryn Roeder , Xingguo Li , and Tuo Zhao

Documentation:   PDF Manual  

GPL-2 license

Imports Rcpp

Depends on splines

Linking to Rcpp, RcppEigen

Imported by pgraph.

See at CRAN