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.

Author
Bradley Efron [aut], Balasubramanian Narasimhan [aut, cre]
Date of publication
2016-12-01 19:44:32
Maintainer
Balasubramanian Narasimhan <naras@stat.Stanford.EDU>
License
GPL (>= 2)
Version
1.0-3
URLs

View on CRAN

Man pages

bardWordCount
Shakespeare word counts in the entire canon: 14,376 distinct...
deconv
A function to compute Empirical Bayes estimates using...
deconvolveR
R package for Empirical Bayes g-modeling using exponential...
disjointTheta
A set of Theta values that have a bimodal distribution for...
surg
Intestinal surgery data involving 844 cancer patients. The...

Files in this package

deconvolveR
deconvolveR/inst
deconvolveR/inst/doc
deconvolveR/inst/doc/deconvolution.Rmd
deconvolveR/inst/doc/deconvolution.R
deconvolveR/inst/doc/deconvolution.html
deconvolveR/NAMESPACE
deconvolveR/data
deconvolveR/data/surg.rda
deconvolveR/data/bardWordCount.rda
deconvolveR/data/disjointTheta.rda
deconvolveR/R
deconvolveR/R/deconvolveR.R
deconvolveR/R/deconv.R
deconvolveR/vignettes
deconvolveR/vignettes/deconvolution.Rmd
deconvolveR/README.md
deconvolveR/MD5
deconvolveR/build
deconvolveR/build/vignette.rds
deconvolveR/DESCRIPTION
deconvolveR/man
deconvolveR/man/bardWordCount.Rd
deconvolveR/man/disjointTheta.Rd
deconvolveR/man/surg.Rd
deconvolveR/man/deconvolveR.Rd
deconvolveR/man/deconv.Rd