168 citations · 1.5k across the 73 of their papers we have counts for
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math.ST2014★ 2 cited
Valid uncertainty quantification about the model in a linear regression setting
Ryan Martin, Huiping Xu, Zuoyi Zhang +1
In scientific applications, there often are several competing models that could be fit to the observed data, so quantification of the model uncertainty is of fundamental importance…
math.ST2014★ 17 cited
Frameworks for prior-free posterior probabilistic inference
Chuanhai Liu, Ryan Martin
The development of statistical methods for valid and efficient probabilistic inference without prior distributions has a long history. Fisher's fiducial inference is perhaps the mo…
math.ST2014★ 75 cited
Empirical Bayes posterior concentration in sparse high-dimensional linear models
Ryan Martin, Raymond Mess, Stephen G. Walker
We propose a new empirical Bayes approach for inference in the normal linear model. The novelty is the use of data in the prior in two ways, for centering and regularizat…