Peer-reviewed papers
Note:The links for "Time capsuled code" provide code for reproducing the numerical results of each paper.
† Graduate student working under my supervision
∗ Undergraduate student working under my supervision
Accepted preprints
- N Dey†, M Singer†, J P Williams, and S Sengupta (202x). Word Embeddings as Statistical Estimators. To appear in Sankhya B.
Link: Manuscript. - V V Volpe, E B Kendall†, A N Collins, M G Graham, J P Williams, and S J Holochwost (202x). Prior exposure to racial discrimination and patterns of acute parasympathetic nervous system responses among black adults. To appear in Psychophysiology.
Link: Manuscript. - E B Kendall†, J P Williams, G H Hermansen, F Bois, and V H Thanh (202x). Beyond time-homogeneity for continuous-time multistate Markov models. To appear in Journal of Computational and Graphical Statistics.
Link: Manuscript. - N Dey†, R Martin, and J P Williams (202x). Neil Dey, Ryan Martin, and Jonathan P Williams' contribution to the Discussion of "Safe Testing" by Grünwald, de Heide, and Koolen. To appear in Journal of the Royal Statistical Society: Series B.
2024
- J Hickey†, J P Williams, and E C Hector (2024). Transfer Learning with Uncertainty Quantification: Random Effect Calibration of Source to Target (RECaST). Journal of Machine Learning Research 25 (338) pp.1-40.
Link: Manuscript. - J P Williams and Y Liu (2024). Decision theory via model-free generalized fiducial inference. Belief Functions: Theory and Applications. Lecture Notes in Computer Science (vol. 14909). Springer.
Link: Manuscript. - R Martin and J P Williams (2024). Large-sample theory for inferential models: A possibilistic Bernstein–von Mises theorem. Belief Functions: Theory and Applications. Lecture Notes in Computer Science (vol. 14909). Springer.
Link: Manuscript. - A Hjort†, J P Williams, and J Pensar (2024). Clustered conformal prediction for the housing market. Proceedings of the Thirteenth Symposium on Conformal and Probabilistic Prediction with Applications, in Proceedings of Machine Learning Research 230 pp.366-386.
Link: Manuscript. - J P Williams, G H Hermansen, H Strand, G Clayton, and H M Nygård (2024). Bayesian hidden Markov models for latent variable labeling assignments in conflict research: application to the role ceasefires play in conflict dynamics. Annals of Applied Statistics 18 (3) pp.2034-2061.
Link: Manuscript. Link: Time capsuled code (R code). - N Giertych†, A Shaban, P Haravu∗, and J P Williams (2024). A statistical primer on classical
period-finding techniques in astronomy. Reports on Progress in Physics 87 (7) 078401 pp.1-18.
Link: Manuscript. Link: Time capsuled code (Python and R code). - A Murph†, J Hannig, and J P Williams (2024). Introduction to generalized fiducial inference. Handbook of Bayesian, Fiducial, and Frequentist Inference (1st ed.). Chapman and Hall/CRC.
Link: Manuscript. Link: Time capsuled code (R code).
2023
- M A Abba†, J P Williams, and B J Reich (2023). A penalized complexity prior for deep Bayesian transfer learning with application to materials informatics. Annals of Applied Statistics 17 (4) pp.3241–3256.
Link: Manuscript. - N Dey†, J Ding†, J Ferrell∗, C Kapper∗, M Lovig∗, E Planchon∗, and J P Williams (2023). Conformal prediction for text infilling and part-of-speech prediction. New England Journal of Statistics in Data Science 1 pp.69-83.
Link: Manuscript. Link: Time capsuled code (Julia code and Python code). - S Koner† and J P Williams (2023). The EAS approach to variable selection for multivariate response data in high-dimensional settings. Electronic Journal of Statistics 17 (2) pp.1947-1995.
Link: Manuscript. Link: Time capsuled code (R code). - J P Williams, D M Ommen, and J Hannig (2023). Generalized fiducial factor: an alternative to the Bayes factor for forensic identification of source problems. Annals of Applied Statistics 17 (1) pp.378–402.
Link: Manuscript. Link: Time capsuled code (R code). - J P Williams, Y Xie, and J Hannig (2023). The EAS approach for graphical selection consistency in vector autoregression models. Canadian Journal of Statistics 51 (2) pp.674-703.
Link: Manuscript. Link: Supplementary material. Link: Time capsuled code (mostly Python code, some R code).
2021
- J P Williams (2021). Discussion of
A Gibbs sampler for a class of random convex polytopes
. Journal of the American Statistical Association 116 (535) pp.1198-1200.
Link: Manuscript. - S Nghiem, J P Williams, C Afoakwah, Q Huynh, S K Ng, and J Byrnes (2021). Can administrative health data improve the gold standard? Evidence from a model of the progression of myocardial infarction. International Journal of Environmental Research and Public Health 18 (14) pp.7385.
Link: Manuscript.
2020
- J P Williams, C B Storlie, T M Therneau, C R Jack Jr, and J Hannig (2020). A Bayesian approach to multi-state hidden Markov models: application to dementia progression. Journal of the American Statistical Association 115 (529) pp.16-31.
Link: Manuscript. Link: Supplementary material. Link: Time capsuled code (R code).
2019
- J P Williams and J Hannig (2019). Nonpenalized variable selection in high-dimensional linear model settings via generalized fiducial inference. Annals of Statistics 47 (3) pp.1723-1753.
Link: Manuscript. Link: Supplementary material. Link: Time capsuled code (mostly Python code, some R code). - E Sechi, E Shosha, J P Williams, S J Pittock, B G Weinshenker, B M Keegan, N L Zalewski, A S Lopez-Chiriboga, J Jitprapaikulsan, and E P Flanagan (2019). Aquaporin-4 and MOG autoantibody discovery in idiopathic transverse myelitis epidemiology. Neurology 93 (4) pp.e414-e420.
Link: Manuscript.
2018
- I Carmichael and J P Williams (2018). An exposition of the false confidence theorem. Stat 7 (1) pp.e201.
Link: Manuscript. Link: Time capsuled code (R code).
2015
- J P Williams and Y Lu (2015). Covariance Selection in the Linear Mixed Effect Model. Journal of Machine Learning Research: Workshop and Conference Proceedings 44 pp.277-291. (NIPS conference session).
Link: Manuscript. Link: Time capsuled code (R code).
Preprints
- J Hickey†, J P Williams, B J Reich, and E C Hector (202x). Multivariate and online transfer learning with uncertainty quantification. In review.
Link: Manuscript. - D Randahl, J P Williams, and H Hegre (202x). Bin-conditional conformal prediction of fatalities from armed conflict. In review.
Link: Manuscript. - N Dey†, R Martin, and J P Williams (202x). Anytime-valid generalized universal inference on risk minimizers. R&R Journal of the Royal Statistical Society: Series B.
Link: Manuscript. - J P Williams (202x). Model-free generalized fiducial inference. R&R Journal of Machine learning Research.
Link: Manuscript. Link: Time capsuled code (Julia code). - N Dey† and J P Williams (202x). Valid inference for machine learning model parameters. In review.
Link: Manuscript. - A Murph†, J Hannig, and J P Williams (202x). Generalized fiducial inference on differentiable manifolds. In review.
Link: Manuscript. - M A Abba†, J P Williams, and B J Reich (202x). A Bayesian shrinkage estimator for transfer learning. In review.
Link: Manuscript. - A Hjort†, G H Hermansen, J Pensar, and J P Williams (202x). Uncertainty quantification in automated valuation models with locally weighted conformal prediction. In review.
Link: Manuscript. - A Murph†, C B Storlie, P M Wilson, J P Williams, and J Hannig (202x). Bayes Watch: Bayesian Change-point Detection for Process Monitoring with Fault Detection. In review.
Link: Manuscript. - I Carmichael, T Keefe, N Giertych†, and J P Williams (202x). yaglm: a Python package for fitting and tuning generalized linear models that supports structured, adaptive and non-convex penalties. In progress.
Link: Manuscript.