activity
20192023
most citedNew Development of Bayesian Variable Selection Criteria for Spatial Point Process with Applications

8 citations · 32 across the 17 of their papers we have counts for

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13 papers · 1 filter

stat.AP2023

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…

stat.AP20202 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.AP20201 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

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.AP20201 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.AP20205 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…