141 citations · 160 across the 9 of their papers we have counts for
9 papers
Highly Scalable Maximum Likelihood and Conjugate Bayesian Inference for ERGMs on Graph Sets with Equivalent Vertices
Fan Yin, Carter T. Butts
The exponential family random graph modeling (ERGM) framework provides a flexible approach for the statistical analysis of networks. As ERGMs typically involve normalizing factors…
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…
Bayesian Analysis of Static Light Scattering Data for Globular Proteins
Fan Yin, Domarin Khago, Rachel W. Martin +1
Static light scattering is a popular physical chemistry technique that enables calculation of physical attributes such as the radius of gyration and the second virial coefficient f…
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 Heterogeneity Can Lead to Substantial Local Variations in COVID-19 Timing and Severity
Loring J. Thomas, Peng Huang, Fan Yin +4
Standard epidemiological models for COVID-19 employ variants of compartment (SIR) models at local scales, implicitly assuming spatially uniform local mixing. Here, we examine the e…
Kernel-based Approximate Bayesian Inference for Exponential Family Random Graph Models
Fan Yin, Carter T. Butts
Bayesian inference for exponential family random graph models (ERGMs) is a doubly-intractable problem because of the intractability of both the likelihood and posterior normalizing…
Finite Mixtures of ERGMs for Modeling Ensembles of Networks
Fan Yin, Weining Shen, Carter T. Butts
Ensembles of networks arise in many scientific fields, but there are few statistical tools for inferring their generative processes, particularly in the presence of both dyadic dep…
Selection of Exponential-Family Random Graph Models via Held-Out Predictive Evaluation (HOPE)
Fan Yin, Nolan Edward Phillips, Carter T. Butts
Statistical models for networks with complex dependencies pose particular challenges for model selection and evaluation. In particular, many well-established statistical tools for…
Comparisons of penalized least squares methods by simulations
Ke Zhang, Fan Yin, Shifeng Xiong
Penalized least squares methods are commonly used for simultaneous estimation and variable selection in high-dimensional linear models. In this paper we compare several prevailing…