50 citations · 93 across the 12 of their papers we have counts for
13 papers
Bias-correction and Test for Mark-point Dependence with Replicated Marked Point Processes
Ganggang Xu, Jingfei Zhang, Yehua Li +1
Mark-point dependence plays a critical role in research problems that can be fitted into the general framework of marked point processes. In this work, we focus on adjusting for ma…
Row-clustering of a Point Process-valued Matrix
Lihao Yin, Ganggang Xu, Huiyan Sang +1
Structured point process data harvested from various platforms poses new challenges to the machine learning community. By imposing a matrix structure to repeatedly observed marked…
Test of Weak Separability for Spatially Stationary Functional Field
Decai Liang, Hui Huang, Yongtao Guan +1
For spatially dependent functional data, a generalized Karhunen-Loève expansion is commonly used to decompose data into an additive form of temporal components and spatially correl…
Second order semi-parametric inference for multivariate log Gaussian Cox processes
Kristian Bjørn Hessellund, Ganggang Xu, Yongtao Guan +1
This paper introduces a new approach to inferring the second order properties of a multivariate log Gaussian Cox process (LGCP) with a complex intensity function. We assume a semi-…
Latent Network Structure Learning from High Dimensional Multivariate Point Processes
Biao Cai, Jingfei Zhang, Yongtao Guan
Learning the latent network structure from large scale multivariate point process data is an important task in a wide range of scientific and business applications. For instance, w…
Group Network Hawkes Process
Guanhua Fang, Ganggang Xu, Haochen Xu +2
In this work, we study the event occurrences of individuals interacting in a network. To characterize the dynamic interactions among the individuals, we propose a group network Haw…
Spatiotemporal Calibration of Atmospheric Nitrogen Dioxide Concentration Estimates From an Air Quality Model for Connecticut
Owais Gilani, Lisa A. McKay, Timothy G. Gregoire +3
A spatiotemporal calibration and resolution refinement model was fitted to calibrate nitrogen dioxide (NO) concentration estimates from the Community Multiscale Air Quality (CM…
Learning Human Activity Patterns using Clustered Point Processes with Active and Inactive States
Jingfei Zhang, Biao Cai, Xuening Zhu +3
Modeling event patterns is a central task in a wide range of disciplines. In applications such as studying human activity patterns, events often arrive clustered with sporadic and…
Orthogonal series estimation of the pair correlation function of a spatial point process
Abdollah Jalilian, Yongtao Guan, Rasmus Waagepetersen
The pair correlation function is a fundamental spatial point process characteristic that, given the intensity function, determines second order moments of the point process. Non-pa…
Towards optimal Takacs--Fiksel estimation
Jean-François Coeurjolly, Yongtao Guan, Mahdieh Khanmohammadi +1
The Takacs--Fiksel method is a general approach to estimate the parameters of a spatial Gibbs point process. This method embraces standard procedures such as the pseudolikelihood a…
Joint modeling of longitudinal drug using pattern and time to first relapse in cocaine dependence treatment data
Jun Ye, Yehua Li, Yongtao Guan
An important endpoint variable in a cocaine rehabilitation study is the time to first relapse of a patient after the treatment. We propose a joint modeling approach based on functi…
Estimating daily nitrogen dioxide level: Exploring traffic effects
Lixun Zhang, Yongtao Guan, Brian P. Leaderer +1
Data used to assess acute health effects from air pollution typically have good temporal but poor spatial resolution or the opposite. A modified longitudinal model was developed th…
Quasi-likelihood for Spatial Point Processes
Yongtao Guan, Abdollah Jalilian, Rasmus Waagepetersen
Fitting regression models for intensity functions of spatial point processes is of great interest in ecological and epidemiological studies of association between spatially referen…