| A Bayesian approach to multistate hidden Markov models: application to dementia progression JP Williams, CB Storlie, TM Therneau, CRJ Jr, J Hannig Journal of the American Statistical Association 115 (529), 16-31, 2020 | 42 | 2020 |
| Aquaporin-4 and MOG autoantibody discovery in idiopathic transverse myelitis epidemiology E Sechi, E Shosha, JP Williams, SJ Pittock, BG Weinshenker, BM Keegan, ... Neurology 93 (4), e414-e420, 2019 | 29 | 2019 |
| Nonpenalized variable selection in high-dimensional linear model settings via generalized fiducial inference JP Williams, J Hannig The Annals of Statistics 47 (3), 1723-1753, 2019 | 20 | 2019 |
| An exposition of the false confidence theorem I Carmichael, J Williams Stat 7 (1), e201, 2018 | 10 | 2018 |
| Introduction to generalized fiducial inference AC Murph, J Hannig, JP Williams Handbook of Bayesian, Fiducial, and Frequentist Inference, 276-299, 2024 | 9 | 2024 |
| The EAS approach for graphical selection consistency in vector autoregression models JP Williams, Y Xie, J Hannig Canadian Journal of Statistics 51 (2), 674-703, 2023 | 8 | 2023 |
| The EAS approach to variable selection for multivariate response data in high-dimensional settings S Koner, JP Williams Electronic Journal of Statistics 17 (2), 1947-1995, 2023 | 5 | 2023 |
| Conformal prediction for text infilling and part-of-speech prediction N Dey, J Ding, J Ferrell, C Kapper, M Lovig, E Planchon, JP Williams The New England Journal of Statistics in Data Science, 2022 | 5 | 2022 |
| Generalized fiducial factor: An alternative to the Bayes factor for forensic identification of source problems JP Williams, DM Ommen, J Hannig The Annals of Applied Statistics 17 (1), 378-402, 2023 | 4 | 2023 |
| Covariance Selection in the Linear Mixed Effect Model JP Williams, Y Lu Journal of Machine Learning Research: Workshop and Conference Proceedings 44 …, 2015 | 4 | 2015 |
| Anytime-Valid Generalized Universal Inference on Risk Minimizers N Dey, R Martin, JP Williams arXiv preprint arXiv:2402.00202, 2024 | 2 | 2024 |
| A penalized complexity prior for deep Bayesian transfer learning with application to materials informatics MA Abba, JP Williams, BJ Reich The Annals of Applied Statistics 17 (4), 3241-3256, 2023 | 2 | 2023 |
| Transfer learning with uncertainty quantification: Random effect calibration of source to target (RECaST) J Hickey, JP Williams, EC Hector arXiv preprint arXiv:2211.16557, 2022 | 2 | 2022 |
| Bayesian hidden Markov models for latent variable labeling assignments in conflict research: application to the role ceasefires play in conflict dynamics JP Williams, GH Hermansen, H Strand, G Clayton, HM Nygård The Annals of Applied Statistics 18 (3), 2034-2061, 2024 | 1* | 2024 |
| Word Embeddings as Statistical Estimators N Dey, M Singer, JP Williams, S Sengupta Sankhya B, 1-27, 2024 | 1 | 2024 |
| Large-sample theory for inferential models: a possibilistic Bernstein--von Mises theorem R Martin, JP Williams arXiv preprint arXiv:2404.15843, 2024 | 1 | 2024 |
| Model-free generalized fiducial inference JP Williams arXiv preprint arXiv:2307.12472, 2023 | 1 | 2023 |
| Valid Inference for Machine Learning Model Parameters N Dey, JP Williams arXiv preprint arXiv:2302.10840, 2023 | 1 | 2023 |
| Generalized Fiducial Inference on Differentiable Manifolds AC Murph, J Hannig, JP Williams arXiv preprint arXiv:2209.15473, 2022 | 1 | 2022 |
| Discussion of “A Gibbs sampler for a class of random convex polytopes” JP Williams Journal of the American Statistical Association 116 (535), 1198-1200, 2021 | 1 | 2021 |
Jan HannigProfessor of Statistics, University of North Carolina在 unc.edu 的电子邮件经过验证
