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20192026
most citedGeographically Weighted Cox Regression for Prostate Cancer Survival Data in Louisiana

23 citations · 153 across the 33 of their papers we have counts for

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Showing 2020Show all

21 papers · 1 filter

stat.ME2020

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…

stat.ME2020

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…

stat.AP2020★ 2 cited

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…

stat.ME2020★ 2 cited

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…

stat.ME2020

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…

stat.ME2020★ 1 cited

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…

stat.AP2020★ 1 cited

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…

stat.AP2020★ 1 cited

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…

stat.AP2020★ 7 cited

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…

stat.AP2020★ 1 cited

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…

stat.ME2020

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…

stat.AP2020★ 5 cited

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…

stat.AP2020★ 22 cited

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…

stat.AP2020

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…

stat.ME2020★ 2 cited

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.…

stat.ME2020

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…

stat.ME2020★ 5 cited

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…

stat.AP2020★ 11 cited

Bayesian Spatial Homogeneity Pursuit for Survival Data with an Application to the SEER Respiratory Cancer Data

Lijiang Geng, Guanyu Hu

In this work, we propose a new Bayesian spatial homogeneity pursuit method for survival data under the proportional hazards model to detect spatially clustered patterns in baseline…

stat.AP2020★ 2 cited

A comparison of Bayesian accelerated failure time models with spatially varying coefficients

Guanyu Hu, Yishu Xue, Fred Huffer

The accelerated failure time (AFT) model is a commonly used tool in analyzing survival data. In public health studies, data is often collected from medical service providers in dif…

stat.ME2020★ 8 cited

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…

stat.AP2020★ 2 cited

Bayesian Spatial Homogeneity Pursuit of Functional Data: an Application to the U.S. Income Distribution

Guanyu Hu, Junxian Geng, Yishu Xue +1

An income distribution describes how an entity's total wealth is distributed amongst its population. A problem of interest to regional economics researchers is to understand the sp…