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>).

Package details

AuthorBradley Efron [aut], Balasubramanian Narasimhan [aut, cre]
MaintainerBalasubramanian Narasimhan <naras@stat.Stanford.EDU>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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deconvolveR documentation built on Aug. 30, 2020, 9:07 a.m.