bnaras/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. Details and examples are in the paper by Narasimhan and Efron (2020, <doi:10.18637/jss.v094.i11>).

Getting started

Package details

Maintainer
LicenseGPL (>= 2)
Version1.2-1
URL https://bnaras.github.io/deconvolveR/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("bnaras/deconvolveR")
bnaras/deconvolveR documentation built on Aug. 31, 2020, 2:53 a.m.