Package: deconvolveR
Title: Empirical Bayes Estimation Strategies
Version: 1.2-1
VignetteBuilder: knitr
Suggests: cowplot, ggplot2, knitr, rmarkdown
Authors@R: c(person("Bradley", "Efron", role=c("aut"),
	   	    email = "brad@stat.stanford.edu"),
  	     person("Balasubramanian", "Narasimhan", role=c("aut", "cre"),
	   	    email = "naras@stat.Stanford.EDU"))
Description: Empirical Bayes methods for learning prior distributions from data.
    An unknown prior distribution (g) has yielded (unobservable) parameters, each of
    which produces a data point from a parametric exponential family (f). The goal
    is to estimate the unknown prior ("g-modeling") by deconvolution and Empirical
    Bayes methods. Details and examples are in the paper by Narasimhan and Efron
    (2020, <doi:10.18637/jss.v094.i11>).
URL: https://bnaras.github.io/deconvolveR/
BugReports: https://github.com/bnaras/deconvolveR/issues
Encoding: UTF-8
Depends: R (>= 3.0)
License: GPL (>= 2)
LazyData: true
Imports: splines, stats
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-08-29 15:42:18 UTC; naras
Author: Bradley Efron [aut],
  Balasubramanian Narasimhan [aut, cre]
Maintainer: Balasubramanian Narasimhan <naras@stat.Stanford.EDU>
Repository: CRAN
Date/Publication: 2020-08-30 01:00:26 UTC
Built: R 4.2.0; ; 2022-06-02 10:38:56 UTC; unix
