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The lava estimation is used to recover signals that is the sum of a sparse signal and a dense signal. The post-lava method corrects the shrinkage bias of lava. For more information on the lava estimation, see Chernozhukov, Hansen, and Liao (2017) <doi:10.1214/16-AOS1434>.
| Version: | 1.0.2 |
| Depends: | Lavash |
| Imports: | pracma, CVXR |
| Published: | 2021-06-04 |
| DOI: | 10.32614/CRAN.package.LavaCvxr |
| Author: | Victor Chernozhukov [aut, cre], Christian Hansen [aut, cre], Yuan Liao [aut, cre], Jaeheon Jung [ctb, cre], Yang Liu [ctb, cre] |
| Maintainer: | Yang Liu <yl1241 at economics.rutgers.edu> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | LavaCvxr results |
| Reference manual: | LavaCvxr.pdf |
| Package source: | LavaCvxr_1.0.2.tar.gz |
| Windows binaries: | r-devel: LavaCvxr_1.0.2.zip, r-release: LavaCvxr_1.0.2.zip, r-oldrel: LavaCvxr_1.0.2.zip |
| macOS binaries: | r-release (arm64): LavaCvxr_1.0.2.tgz, r-oldrel (arm64): LavaCvxr_1.0.2.tgz, r-release (x86_64): LavaCvxr_1.0.2.tgz, r-oldrel (x86_64): LavaCvxr_1.0.2.tgz |
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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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