Working papers, etc.

L. Cella and R. Martin. Valid inferential models for prediction in supervised learning problems. [pdf]

N. Syring and R. Martin. Stochastic optimization for numerical evaluation of imprecise probabilities. [arXiv]

R. Martin. An impreciseprobabilistic characterization of frequentist statistical inference. [researchers.one]

R. Martin. Asymptotically optimal inference in sparse sequence models with a simple datadependent measure. [researchers.one] [arXiv]

N. Syring and R. Martin. Gibbs posterior concentration rates under subexponential type losses. [arXiv]

P.S. Wu and R. Martin. A comparison of learning rate selection methods in generalized Bayesian inference. [arXiv]

L. Cella and R. Martin. Validity, consonant plausibility measures, and conformal prediction. [researchers.one] [arXiv]

V. Dixit and R. Martin. Estimating a mixing distribution on the sphere using predictive recursion. [researchers.one] [arXiv]

C. Liu and R. Martin. Inferential models and possibility measures. [researchers.one] [arXiv]

R. Martin, M. Balch, and S. Ferson. Response to the comment ("Confidence in confidence distributions!") by Cunen, Hjort, and Schweder. [researchers.one]

C. Liu, R. Martin, and W. Shen. Empirical priors and posterior concentration in a piecewise polynomial sequence model. [arXiv]

Y. Yang and R. Martin. Variational approximations of empirical Bayes posteriors in highdimensional linear models. [arXiv]

H. Mao, R. Martin, and B. Reich. Valid modelfree spatial prediction. [researchers.one] [arXiv]

I. Bhattacharya and R. Martin. Gibbs posterior inference on multivariate quantiles. [arXiv]

C. Liu and R. Martin. An empirical GWishart prior for sparse highdimensional Gaussian graphical models. [arXiv]

J. Cahoon and R. Martin. Generalized inferential models for censored data. [researchers.one] [arXiv]

V. Dixit and R. Martin. Permutationbased uncertainty quantification about a mixing distribution. [arXiv]