Nicholas Syring @ WUSTL–Department of Mathematics and Statistics : Research

Research areas

I work in several areas of statistics theory and methodology including Bayesian and pseudo-Bayesian statistics, foundations of statistical inference, and post-selection inference. Links to my published papers and drafts may be found below.
N. Syring and R. Martin. Robust and Rate-Optimal Gibbs Posterior Inference on the Boundary of a Noisy Image. Annals of Statistics. (2019). Accepted.

R. Martin and N. Syring. Validity-preservation properties of rules for combining inferential models. Proceedings of the Eleventh International Symposium on Imprecise Probabilities: Theories and Applications, in Proceedings of Machine Learning Research. (2019), 103:286-294. http://proceedings.

N. Syring and R. Martin. Calibrating General Posterior Credible Regions. Biometrika. (2018).

N. Syring L. Hong, and R. Martin. Gibbs Posterior Inference on Value-at-Risk. Scandinavian Actuarial Journal. (2019).

N. Syring and R. Martin. Gibbs Posterior Inference on the Minimum Clinically Important Difference. Journal of Statistical Planning and Inference. 187 (2017): 67-77.

C. Liu, R. Martin, and N. Syring. Efficient Simulation from a Gamma Distribution with Small Shape Parameter. Computational Statistics 32, 4 (2017): 1767-1775.

N. Syring and M. Li. BayesBD: An R Package for Bayesian Inference on Image Boundaries. R Journal. 9, 2 (2017): 149-162.