Archive
Software for estimating the local false discovery rate
Recent preprints by David Bickel
Evidential unification of confidence and empirical Bayes methods
D. R. Bickel, “Confidence distributions and empirical Bayes posterior distributions unified as distributions of evidential support,” Working Paper, DOI: 10.5281/zenodo.2529438, http://doi.org/10.5281/zenodo.2529438 (2018). 2018 preprint
Fiducial model averaging of Bayesian models and of frequentist models
D. R. Bickel, “A note on fiducial model averaging as an alternative to checking Bayesian and frequentist models,” Communications in Statistics – Theory and Methods 47, 3125-3137 (2018). Full article | 2015 preprint
How to choose features or p values for empirical Bayes estimation of the local false discovery rate
F. Abbas-Aghababazadeh, M. Alvo, and D. R. Bickel, “Estimating the local false discovery rate via a bootstrap solution to the reference class problem,” PLoS ONE 13, e0206902 (2018) | full text | 2016 preprint
R functions for combining probabilities using game theory
Suite of R functions for combination of probabilities using a game-theoretic method
Why adjust priors for the simplicity of data distributions?
D. R. Bickel, “An explanatory rationale for priors sharpened into Occam’s razors,” Working Paper, DOI: 10.5281/zenodo.1412875, https://doi.org/10.5281/zenodo.1412875 (2018). 2018 preprint
David Bickel, statistician 
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