DESCRIPTION

Package: smashr
Encoding: UTF-8
Type: Package
Maintainer: Peter Carbonetto <pcarbo@uchicago.edu>
Authors@R: c(person("Zhengrong","Xing",role="aut"),
	     person("Matthew","Stephens",role="aut"),
	     person("Kaiqian","Zhang",role="ctb"),
             person("Peter","Carbonetto",role=c("aut","cre"),
	            email="pcarbo@uchicago.edu"))
Title: Smoothing by Adaptive Shrinkage in R
Version: 1.2-9
Date: 2021-06-07
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 & M. Stephens,
    2016 <arXiv:1605.07787>.
License: GPL (>= 3)
Depends: R (>= 3.1.1),
Imports:
    utils,
    stats,
    Rcpp (>= 0.11.1),
    data.table,
    caTools,
    wavethresh,
    ashr
Suggests:
    knitr,
    rmarkdown,
    MASS,
    EbayesThresh,
    testthat
LinkingTo: Rcpp
NeedsCompilation: yes
LazyData: true
URL: http://github.com/stephenslab/smashr
BugReports: http://github.com/stephenslab/smashr/issues
VignetteBuilder: knitr
RoxygenNote: 7.1.1