23 citations · 153 across the 33 of their papers we have counts for
34 papers
Beyond Match Results: Bayesian Mediation of Ability, Performance, and Winning in Professional Tennis
Guanyu Hu, Xiao Wang
Match results measure competitive ability, but they do not explain how ability is expressed during play. Match statistics offer a natural mediator, however performance is usually m…
Functional Causal Inference with Time-to-Event Data
Xiyuan Gao, Jiayi Wang, Guanyu Hu +1
Functional data is a powerful tool for capturing and analyzing complex patterns and relationships in a variety of fields, allowing for more precise modeling, visualization, and dec…
A Continuous-Time Stochastic Process for High-Resolution Network Data in Sports
Nicholas Grieshop, Yong Feng, Guanyu Hu +1
Technological advances have paved the way for collecting high-resolution network data in basketball, football, and other team-based sports. Such data consist of interactions among…
Precision education: A Bayesian nonparametric approach for handling item and examinee heterogeneity in assessment data
Tianyu Pan, Weining Shen, Clintin P. Davis-Stober +1
We propose a novel nonparametric Bayesian IRT model in this paper by introducing the clustering effect at question level and further assume heterogeneity at examinee level under ea…
Multidimensional heterogeneity learning for count value tensor data with applications to field goal attempt analysis of NBA players
Guanyu Hu, Yishu Xue, Weining Shen
We propose a multidimensional tensor clustering approach for studying how professional basketball players' shooting patterns vary over court locations and game time. Unlike most ex…
How Much Does Home Field Advantage Matter in Soccer Games? A Causal Inference Approach for English Premier League Analysis
Chen Wang, Katherine Price, Hengrui Cai +3
In many sports, it is commonly believed that the home team has an advantage over the visiting team, known as the home field advantage. Yet its causal effect on team performance is…
Graphical Assistant Grouped Network Autoregression Model: a Bayesian Nonparametric Recourse
Yimeng Ren, Xuening Zhu, Guanyu Hu
Vector autoregression model is ubiquitous in classical time series data analysis. With the rapid advance of social network sites, time series data over latent graph is becoming inc…
Identifying latent groups in spatial panel data using a Markov random field constrained product partition model
Tianyu Pan, Guanyu Hu, Weining Shen
Understanding the heterogeneity over spatial locations is an important problem that has been widely studied in many applications such as economics and environmental science. In thi…
Sample size re-estimation in Phase 2 Dose-Finding: Conditional power vs. Bayesian predictive power
Qingyang Liu, Guanyu Hu, Binqi Ye +2
Unblinded sample size re-estimation (SSR) is often planned in a clinical trial when there is large uncertainty about the true treatment effect. For Proof-of Concept (PoC) in a Phas…
Zero Inflated Poisson Model with Clustered Regression Coefficients: an Application to Heterogeneity Learning of Field Goal Attempts of Professional Basketball Players
Guanyu Hu, Hou-Cheng Yang, Yishu Xue +1
Although basketball is a dynamic process sport, with 5 plus 5 players competing on both offense and defense simultaneously, learning some static information is predominant for prof…
Bayesian Nonparametric Estimation for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations
Fan Yin, Jieying Jiao, Guanyu Hu +1
Basketball shot location data provide valuable summary information regarding players to coaches, sports analysts, fans, statisticians, as well as players themselves. Represented by…
Mixture of Finite Mixtures Model for Basket Trial
Junxian Geng, Tianjian Zhou, Ruitao Lin +1
With the recent paradigm shift from cytotoxic drugs to new generation of target therapy and immuno-oncology therapy during oncology drug developments, patients with various cancer…
Analysis of professional basketball field goal attempts via a Bayesian matrix clustering approach
Fan Yin, Guanyu Hu, Weining Shen
We propose a Bayesian nonparametric matrix clustering approach to analyze the latent heterogeneity structure in the shot selection data collected from professional basketball playe…
Spatial homogeneity learning for spatially correlated functional data with application to COVID-19 Growth rate curves
Tianyu Pan, Weining Shen, Guanyu Hu
We study the spatial heterogeneity effect on regional COVID-19 pandemic timing and severity by analyzing the COVID-19 growth rate curves in the United States. We propose a geograph…
Time Fused Coefficient SIR Model with Application to COVID-19 Epidemic in the United States
Hou-Cheng Yang, Yishu Xue, Yuqing Pan +2
In this paper, we propose a Susceptible-Infected-Removal (SIR) model with time fused coefficients. In particular, our proposed model discovers the underlying time homogeneity patte…
Bayesian Variable Selection for Cox Regression Model with Spatially Varying Coefficients with Applications to Louisiana Respiratory Cancer Data
Jinjian Mu, Qingyang Liu, Lynn Kuo +1
The Cox regression model is a commonly used model in survival analysis. In public health studies, clinical data are often collected from medical service providers of different loca…
Heterogeneity Learning for SIRS model: an Application to the COVID-19
Guanyu Hu, Junxian Geng
We propose a Bayesian Heterogeneity Learning approach for Susceptible-Infected-Removal-Susceptible (SIRS) model that allows underlying clustering patterns for transmission rate, re…
Bayesian Hierarchical Spatial Regression Models for Spatial Data in the Presence of Missing Covariates with Applications
Zhihua Ma, Guanyu Hu, Ming-Hui Chen
In many applications, survey data are collected from different survey centers in different regions. It happens that in some circumstances, response variables are completely observe…
Geographically Weighted Regression Analysis for Spatial Economics Data: a Bayesian Recourse
Zhihua Ma, Yishu Xue, Guanyu Hu
The geographically weighted regression (GWR) is a well-known statistical approach to explore spatial non-stationarity of the regression relationship in spatial data analysis. In th…
Bayesian Group Learning for Shot Selection of Professional Basketball Players
Guanyu Hu, Hou-Cheng Yang, Yishu Xue
In this paper, we develop a group learning approach to analyze the underlying heterogeneity structure of shot selection among professional basketball players in the NBA. We propose…
A Nonparametric Bayesian Item Response Modeling Approach for Clustering Items and Individuals Simultaneously
Guanyu Hu, Zhihua Ma, Insu Paek
Item response theory (IRT) is a popular modeling paradigm for measuring subject latent traits and item properties according to discrete responses in tests or questionnaires. There…
Most Likely Optimal Subsampled Markov Chain Monte Carlo
Guanyu Hu, HaiYing Wang
Markov Chain Monte Carlo (MCMC) requires to evaluate the full data likelihood at different parameter values iteratively and is often computationally infeasible for large data sets.…
Bayesian Clustered Coefficients Regression with Auxiliary Covariates Assistant Random Effects
Guanyu Hu, Yishu Xue, Zhihua Ma
In regional economics research, a problem of interest is to detect similarities between regions, and estimate their shared coefficients in economics models. In this article, we pro…
Heterogeneity Pursuit for Spatial Point Pattern with Application to Tree Locations: A Bayesian Semiparametric Recourse
Jieying Jiao, Guanyu Hu, Jun Yan
Spatial point pattern data are routinely encountered. A flexible regression model for the underlying intensity is essential to characterizing the spatial point pattern and understa…