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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 ("gmodeling") by deconvolution and Empirical Bayes methods.
Package details 


Author  Bradley Efron [aut], Balasubramanian Narasimhan [aut, cre] 
Date of publication  20161201 19:44:32 
Maintainer  Balasubramanian Narasimhan <naras@stat.Stanford.EDU> 
License  GPL (>= 2) 
Version  1.03 
URL  http://github.com/bnaras/deconvolveR 
Package repository  View on CRAN 
Installation 
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