23 citations · 153 across the 33 of their papers we have counts for
15 papers · 1 filter
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…
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…
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…
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…
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…
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…
Spatial Clustering Regression of Count Value Data via Bayesian Mixture of Finite Mixtures
Peng Zhao, Hou-Cheng Yang, Dipak K. Dey +1
Investigating relationships between response variables and covariates in areas such as environmental science, geoscience, and public health is an important endeavor. Based on a Bay…
Bayesian Nonparametric Nonhomogeneous Poisson Process with Applications to USGS Earthquake Data
Junxian Geng, Wei Shi, Guanyu Hu
Intensity estimation is a common problem in statistical analysis of spatial point pattern data. This paper proposes a nonparametric Bayesian method for estimating the spatial point…