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>).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2-1 |
2026-04-09 windows/windows R-4.5 | deconvolveR_1.2-1.zip |
1.6 MiB |