deconvolveR

Empirical Bayes Estimation Strategies

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.

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Description file content

Package
deconvolveR
Title
Empirical Bayes Estimation Strategies
Version
1.1
VignetteBuilder
knitr
Suggests
cowplot, ggplot2, knitr, rmarkdown
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.
URL
BugReports
https://github.com/bnaras/deconvolveR/issues
Encoding
UTF-8
Depends
R (>= 3.0)
License
GPL (>= 2)
LazyData
true
Imports
splines, stats
RoxygenNote
6.1.1
NeedsCompilation
no
Packaged
2019-02-08 21:41:34 UTC; naras
Author
Bradley Efron [aut], Balasubramanian Narasimhan [aut, cre]
Maintainer
Balasubramanian Narasimhan
Repository
CRAN
Date/Publication
2019-02-08 22:33:28 UTC

install.packages('deconvolveR')

1.1

4 months ago

https://bnaras.github.io/deconvolveR

Balasubramanian Narasimhan

GPL (>= 2)

Depends on

R (>= 3.0)

Imports

splines, stats

Suggests

cowplot, ggplot2, knitr, rmarkdown

Discussions