Empirical Bayes ranking applicable to parallelestimation settings where the estimated parameters are asymptotically unbiased and normal, with known standard errors. A mixture normal prior for each parameter is estimated using Empirical Bayes methods, subsequentially ranks for each parameter are simulated from the resulting joint posterior over all parameters (The marginal posterior densities for each parameter are assumed independent). Finally, experiments are ordered by expected posterior rank, although computations minimizing other plausible rankloss functions are also given.
Package details 


Author  John Ferguson [aut, cre] 
Maintainer  John Ferguson <[email protected]> 
License  CC0 
Version  1.0.0 
Package repository  View on CRAN 
Installation 
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