Fast, wavelet-based Empirical Bayes shrinkage methods for signal denoising, including smoothing Poisson-distributed data and Gaussian-distributed data with possibly heteroskedastic error. The algorithms implement the methods described Z. Xing, P. Carbonetto & M. Stephens (2021) <https://jmlr.org/papers/v22/19-042.html>.
| Version: | 1.3-12 |
| Depends: | R (≥ 3.1.1) |
| Imports: | utils, stats, data.table, caTools, wavethresh, ashr, Rcpp (≥ 1.1.0) |
| LinkingTo: | Rcpp |
| Suggests: | knitr, rmarkdown, MASS, EbayesThresh, testthat |
| Published: | 2025-12-15 |
| DOI: | 10.32614/CRAN.package.smashr (may not be active yet) |
| Author: | Zhengrong Xing [aut], Matthew Stephens [aut], Kaiqian Zhang [ctb], Daniel Nachun [ctb], Guy Nason [cph], Stuart Barber [cph], Tim Downie [cph], Piotr Frylewicz [cph], Arne Kovac [cph], Todd Ogden [cph], Bernard Silverman [cph], Peter Carbonetto [aut, cre] |
| Maintainer: | Peter Carbonetto <pcarbo at uchicago.edu> |
| BugReports: | https://github.com/stephenslab/smashr/issues |
| License: | GPL (≥ 3) |
| Copyright: | file COPYRIGHTS smashr copyright details |
| URL: | https://github.com/stephenslab/smashr |
| NeedsCompilation: | yes |
| Citation: | smashr citation info |
| Materials: | README |
| CRAN checks: | smashr results |
| Reference manual: | smashr.html , smashr.pdf |
| Package source: | smashr_1.3-12.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): smashr_1.3-12.tgz, r-oldrel (arm64): smashr_1.3-12.tgz, r-release (x86_64): smashr_1.3-12.tgz, r-oldrel (x86_64): not available |
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