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Jonathan P Williams
Jonathan P Williams
Assistant Professor, North Carolina State University
Verified email at ncsu.edu - Homepage
Title
Cited by
Cited by
Year
A Bayesian approach to multistate hidden Markov models: application to dementia progression
JP Williams, CB Storlie, TM Therneau, CR Jack Jr, J Hannig
Journal of the American Statistical Association, 2019
382019
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
272019
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
182019
An exposition of the false confidence theorem
I Carmichael, J Williams
Stat 7 (1), e201, 2018
92018
Introduction to generalized fiducial inference
AC Murph, J Hannig, JP Williams
Handbook of Bayesian, Fiducial, and Frequentist Inference, 276-299, 2024
72024
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
72023
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
52023
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
52022
Covariance Selection in the Linear Mixed Effect Model
JP Williams, Y Lu
Journal of Machine Learning Research: Workshop and Conference Proceedings 44 …, 2015
42015
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
22023
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
22023
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
22022
Word Embeddings as Statistical Estimators
N Dey, M Singer, JP Williams, S Sengupta
arXiv preprint arXiv:2301.06710, 2023
12023
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, HM Nygård, G Clayton, SA Rustad, H Strand
arXiv preprint arXiv:2110.05475, 2021
1*2021
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
12021
A Bayesian shrinkage estimator for transfer learning
MA Abba, JP Williams, BJ Reich
arXiv preprint arXiv:2403.17321, 2024
2024
Anytime-Valid Generalized Universal Inference on Risk Minimizers
N Dey, R Martin, JP Williams
arXiv preprint arXiv:2402.00202, 2024
2024
Uncertainty quantification in automated valuation models with locally weighted conformal prediction
A Hjort, GH Hermansen, J Pensar, JP Williams
arXiv preprint arXiv:2312.06531, 2023
2023
Bayes Watch: Bayesian Change-point Detection for Process Monitoring with Fault Detection
AC Murph, CB Storlie, PM Wilson, JP Williams, J Hannig
arXiv preprint arXiv:2310.02940, 2023
2023
Model-free generalized fiducial inference
JP Williams
arXiv preprint arXiv:2307.12472, 2023
2023
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Articles 1–20