research
∙
08/01/2023
Informed Bayesian Finite Mixture Models via Asymmetric Dirichlet Priors
Finite mixture models are flexible methods that are commonly used for mo...
share
research
∙
02/14/2023
A Projection Approach to Local Regression with Variable-Dimension Covariates
Incomplete covariate vectors are known to be problematic for estimation ...
research
∙
07/13/2022
Nonparametric Bayesian Approach to Treatment Ranking in Network Meta-Analysis with Application to Comparisons of Antidepressants
Network meta-analysis is a powerful tool to synthesize evidence from ind...
research
∙
01/19/2022
Using Joint Random Partition Models for Flexible Change Point Analysis in Multivariate Processes
Change point analyses are concerned with identifying positions of an ord...
research
∙
12/22/2020
A spectral adjustment for spatial confounding
Adjusting for an unmeasured confounder is generally an intractable probl...
research
∙
12/31/2019
Prediction in the Presence of Missing Covariates
In many applied fields incomplete covariate vectors are commonly encount...
research
∙
12/24/2019
Spatio-Temporal Random Partition Models
The number of scientific fields that regularly collect data that are spa...
research
∙
07/10/2019
Bayesian inferences on uncertain ranks and orderings
It is common to be interested in rankings or order relationships among e...
research
∙
09/29/2018
Discovering Interactions Using Covariate Informed Random Partition Models
Combination chemotherapy treatment regimens created for patients diagnos...
research
∙
12/28/2017