research
∙
06/12/2023
Ultra-efficient MCMC for Bayesian longitudinal functional data analysis
Functional mixed models are widely useful for regression analysis with d...
share
research
∙
06/08/2023
Monte Carlo inference for semiparametric Bayesian regression
Data transformations are essential for broad applicability of parametric...
research
∙
10/26/2022
Nonparametric Copula Models for Mixed Data with Informative Missingness
Modern datasets commonly feature both substantial missingness and variab...
research
∙
03/01/2022
Bayesian adaptive and interpretable functional regression for exposure profiles
Pollutant exposures during gestation are a known and adverse factor for ...
research
∙
10/27/2021
Warped Dynamic Linear Models for Time Series of Counts
Dynamic Linear Models (DLMs) are commonly employed for time series analy...
research
∙
10/23/2021
Conjugate priors for count and rounded data regression
Discrete data are abundant and often arise as counts or rounded data. Ye...
research
∙
08/04/2021
Semiparametric Functional Factor Models with Bayesian Rank Selection
Functional data are frequently accompanied by parametric templates that ...
research
∙
07/27/2021
Subset selection for linear mixed models
Linear mixed models (LMMs) are instrumental for regression analysis with...
research
∙
06/16/2021
Semiparametric count data regression for self-reported mental health
"For how many days during the past 30 days was your mental health not go...
research
∙
04/20/2021
Bayesian subset selection and variable importance for interpretable prediction and classification
Subset selection is a valuable tool for interpretable learning, scientif...
research
∙
06/23/2020
Fast, Optimal, and Targeted Predictions using Parametrized Decision Analysis
Prediction is critical for decision-making under uncertainty and lends v...
research
∙
06/27/2019
A Simultaneous Transformation and Rounding Approach for Modeling Integer-Valued Data
We propose a simple yet powerful framework for modeling integer-valued d...
research
∙
06/27/2019
Simultaneous Transformation and Rounding (STAR) Models for Integer-Valued Data
We propose a simple yet powerful framework for modeling integer-valued d...
research
∙
02/20/2019
Integer-Valued Functional Data Analysis for Measles Forecasting
Measles presents a unique and imminent challenge for epidemiologists and...
research
∙
08/20/2018
Bayesian Function-on-Scalars Regression for High Dimensional Data
We develop a fully Bayesian framework for function-on-scalars regression...
research
∙
06/05/2018