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An implementation of the fast structural filtering with L0 penalty. It includes an adaptive polynomial estimator by minimizing the least squares error with constraints on the number of breaks in their (k + 1)-st discrete derivative, for a chosen integer k >= 0. It also includes generalized structure sparsity constraint, i.e., graph trend filtering. This package is implemented via the primal dual active set algorithm, which formulates estimates and residuals as primal and dual variables, and utilizes efficient active set selection strategies based on the properties of the primal and dual variables.
| Version: | 0.1.1 |
| Depends: | R (≥ 3.0.0) |
| Imports: | Rcpp (≥ 0.12.10), limSolve |
| LinkingTo: | Rcpp, RcppArmadillo |
| Published: | 2017-07-19 |
| Author: | Canhong Wen, Xueqin Wang, Yanhe Shen, Aijun Zhang |
| Maintainer: | Canhong Wen <wencanhong at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| CRAN checks: | FastSF results |
| Reference manual: | FastSF.pdf |
| Package source: | FastSF_0.1.1.tar.gz |
| Windows binaries: | r-devel: FastSF_0.1.1.zip, r-release: FastSF_0.1.1.zip, r-oldrel: FastSF_0.1.1.zip |
| macOS binaries: | r-release (arm64): FastSF_0.1.1.tgz, r-oldrel (arm64): FastSF_0.1.1.tgz, r-release (x86_64): FastSF_0.1.1.tgz, r-oldrel (x86_64): FastSF_0.1.1.tgz |
| Old sources: | FastSF archive |
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