Package: smashr Encoding: UTF-8 Type: Package Maintainer: Peter Carbonetto Authors@R: c(person("Zhengrong","Xing",role="aut"), person("Matthew","Stephens",role="aut"), person("Kaiqian","Zhang",role="ctb"), person("Daniel","Nachun",role="ctb"), person("Guy","Nason", role="cph"), person("Stuart","Barber",role="cph"), person("Tim","Downie",role="cph"), person("Piotr","Frylewicz",role="cph"), person("Arne","Kovac",role="cph"), person("Todd","Ogden",role="cph"), person("Bernard","Silverman",role="cph"), person("Peter","Carbonetto",role=c("aut","cre"), email="pcarbo@uchicago.edu")) Title: Smoothing by Adaptive Shrinkage Version: 1.3-12 Date: 2025-12-09 Description: 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) . License: GPL (>= 3) Copyright: file COPYRIGHTS Depends: R (>= 3.1.1), Imports: utils, stats, data.table, caTools, wavethresh, ashr, Rcpp (>= 1.1.0) Suggests: knitr, rmarkdown, MASS, EbayesThresh, testthat LinkingTo: Rcpp NeedsCompilation: yes LazyData: true URL: https://github.com/stephenslab/smashr BugReports: https://github.com/stephenslab/smashr/issues VignetteBuilder: knitr RoxygenNote: 7.3.1 Repository: https://stephenslab.r-universe.dev Date/Publication: 2025-12-09 16:43:52 UTC RemoteUrl: https://github.com/stephenslab/smashr RemoteRef: HEAD RemoteSha: e06efa41a3a523833fc0ee743a34cb02da0f26a7 Packaged: 2026-06-14 08:29:33 UTC; root 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]