168 citations · 1.5k across the 73 of their papers we have counts for
5 papers · 2 filters
Discussion: Foundations of Statistical Inference, Revisited
Ryan Martin, Chuanhai Liu
This is an invited contribution to the discussion on Professor Deborah Mayo's paper, "On the Birnbaum argument for the strong likelihood principle," to appear in Statistical Scienc…
On Posterior Concentration in Misspecified Models
R. V. Ramamoorthi, Karthik Sriram, Ryan Martin
We investigate the asymptotic behavior of Bayesian posterior distributions under independent and identically distributed () misspecified models. More specifically, we study…
Marginal inferential models: prior-free probabilistic inference on interest parameters
Ryan Martin, Chuanhai Liu
The inferential models (IM) framework provides prior-free, frequency-calibrated, posterior probabilistic inference. The key is the use of random sets to predict unobservable auxili…
Asymptotically minimax empirical Bayes estimation of a sparse normal mean vector
Ryan Martin, Stephen G. Walker
For the important classical problem of inference on a sparse high-dimensional normal mean vector, we propose a novel empirical Bayes model that admits a posterior distribution with…
Random sets and exact confidence regions
Ryan Martin
An important problem in statistics is the construction of confidence regions for unknown parameters. In most cases, asymptotic distribution theory is used to construct confidence r…