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Provides the ASUS procedure for estimating a high dimensional sparse parameter in the presence of auxiliary data that encode side information on sparsity. It is a robust data combination procedure in the sense that even when pooling non-informative auxiliary data ASUS would be at least as efficient as competing soft thresholding based methods that do not use auxiliary data. For more information, please see the paper Adaptive Sparse Estimation with Side Information by Banerjee, Mukherjee and Sun (JASA 2020).
Version: | 1.5.0 |
Imports: | wavethresh, stats, utils |
Suggests: | knitr, rmarkdown |
Published: | 2023-08-24 |
DOI: | 10.32614/CRAN.package.asus |
Author: | Trambak Banerjee [aut, cre], Gourab Mukherjee [aut], Wenguang Sun [aut] |
Maintainer: | Trambak Banerjee <trambak at ku.edu> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://github.com/trambakbanerjee/asus#asus |
NeedsCompilation: | no |
Materials: | NEWS |
CRAN checks: | asus results |
Reference manual: | asus.pdf |
Vignettes: |
demo-asus |
Package source: | asus_1.5.0.tar.gz |
Windows binaries: | r-devel: asus_1.5.0.zip, r-release: asus_1.5.0.zip, r-oldrel: asus_1.5.0.zip |
macOS binaries: | r-release (arm64): asus_1.5.0.tgz, r-oldrel (arm64): asus_1.5.0.tgz, r-release (x86_64): asus_1.5.0.tgz, r-oldrel (x86_64): asus_1.5.0.tgz |
Old sources: | asus archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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