research
∙
04/24/2023
Functional Causal Inference with Time-to-Event Data
Functional data is a powerful tool for capturing and analyzing complex p...
share
research
∙
03/02/2023
A Continuous-Time Stochastic Process for High-Resolution Network Data in Sports
Technological advances have paved the way for collecting high-resolution...
research
∙
11/21/2022
Precision education: A Bayesian nonparametric approach for handling item and examinee heterogeneity in assessment data
We propose a novel nonparametric Bayesian IRT model in this paper by int...
research
∙
05/20/2022
Multidimensional heterogeneity learning for count value tensor data with applications to field goal attempt analysis of NBA players
We propose a multidimensional tensor clustering approach for studying ho...
research
∙
05/15/2022
How Much Does Home Field Advantage Matter in Soccer Games? A Causal Inference Approach for English Premier League Analysis
In many sports, it is commonly believed that the home team has an advant...
research
∙
10/11/2021
Graphical Assistant Grouped Network Autoregression Model: a Bayesian Nonparametric Recourse
Vector autoregression model is ubiquitous in classical time series data ...
research
∙
12/29/2020
Sample Size Re-estimation Design in Phase II Dose Finding Study with Multiple Dose Groups: Frequentist and Bayesian Methods
Unblinded sample size re-estimation (SSR) is often planned in a clinical...
research
∙
12/18/2020
Identifying latent groups in spatial panel data using a Markov random field constrained product partition model
Understanding the heterogeneity over spatial locations is an important p...
research
∙
12/12/2020
Zero Inflated Poisson Model with Clustered Regression Coefficients: an Application to Heterogeneity Learning of Field Goal Attempts of Professional Basketball Players
Although basketball is a dynamic process sport, with 5 plus 5 players co...
research
∙
11/23/2020
Bayesian Nonparametric Estimation for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations
Basketball shot location data provide valuable summary information regar...
research
∙
11/09/2020
Mixture of Finite Mixtures Model for Basket Trial
With the recent paradigm shift from cytotoxic drugs to new generation of...
research
∙
10/16/2020
Analysis of professional basketball field goal attempts via a Bayesian matrix clustering approach
We propose a Bayesian nonparametric matrix clustering approach to analyz...
research
∙
08/20/2020
Spatial homogeneity learning for spatially correlated functional data with application to COVID-19 Growth rate curves
We study the spatial heterogeneity effect on regional COVID-19 pandemic ...
research
∙
08/10/2020
Time Fused Coefficient SIR Model with Application to COVID-19 Epidemic in the United States
In this paper, we propose a Susceptible-Infected-Removal (SIR) model wit...
research
∙
08/03/2020
Bayesian Variable Selection for Cox Regression Model with Spatially Varying Coefficients with Applications to Louisiana Respiratory Cancer Data
The Cox regression model is a commonly used model in survival analysis. ...
research
∙
07/16/2020
Heterogeneity Learning for SIRS model: an Application to the COVID-19
We propose a Bayesian Heterogeneity Learning approach for Susceptible-In...
research
∙
07/05/2020
Bayesian Hierarchical Spatial Regression Models for Spatial Data in the Presence of Missing Covariates with Applications
In many applications, survey data are collected from different survey ce...
research
∙
07/05/2020
Geographically Weighted Regression Analysis for Spatial Economics Data: a Bayesian Recourse
The geographically weighted regression (GWR) is a well-known statistical...
research
∙
06/12/2020
Bayesian Group Learning for Shot Selection of Professional Basketball Players
In this paper, we develop a group learning approach to analyze the under...
research
∙
05/29/2020
A Nonparametric Bayesian Item Response Modeling Approach for Clustering Items and Individuals Simultaneously
Item response theory (IRT) is a popular modeling paradigm for measuring ...
research
∙
05/23/2020
Most Likely Optimal Subsampled Markov Chain Monte Carlo
Markov Chain Monte Carlo (MCMC) requires to evaluate the full data likel...
research
∙
04/25/2020
Bayesian Clustered Coefficients Regression with Auxiliary Covariates Assistant Random Effects
In regional economics research, a problem of interest is to detect simil...
research
∙
03/23/2020
Heterogeneity Pursuit for Spatial Point Pattern with Application to Tree Locations: A Bayesian Semiparametric Recourse
Spatial point pattern data are routinely encountered. A flexible regress...
research
∙
03/06/2020
Bayesian Spatial Homogeneity Pursuit for Survival Data with an Application to the SEER Respiration Cancer
In this work, we propose a new Bayesian spatial homogeneity pursuit meth...
research
∙
02/16/2020
Bayesian Spatial Homogeneity Pursuit Regression for Count Value Data
Spatial regression models are ubiquitous in many different areas such as...
research
∙
02/16/2020
Bayesian Spatial Homogeneity Pursuit of Functional Data: an Application to the U.S. Income Distribution
An income distribution describes how an entity's total wealth is distrib...
research
∙
02/08/2020
A comparison of Bayesian accelerated failure time models with spatially varying coefficients
The accelerated failure time (AFT) model is a commonly used tool in anal...
research
∙
12/08/2019
Spatial Weibull Regression with Multivariate Log Gamma Process and Its Applications to China Earthquake Economic Loss
Bayesian spatial modeling of heavy-tailed distributions has become incre...
research
∙
10/15/2019
New Development of Bayesian Variable Selection Criteria for Spatial Point Process with Applications
Selecting important spatial-dependent variables under the nonhomogeneous...
research
∙
08/24/2019
Geographically Weighted Cox Regression for Prostate Cancer Survival Data in Louisiana
The Cox proportional hazard model is one of the most popular tools in an...
research
∙
08/15/2019
A Bayesian Joint Model for Spatial Point Processes with Application to Basketball Shot Chart
The success rate of a basketball shot may be higher at locations where a...
research
∙
07/06/2019
Bayesian Nonparametric Nonhomogeneous Poisson Process with Applications to USGS Earthquake Data
Intensity estimation is a common problem in statistical analysis of spat...
research
∙
07/04/2019
