most citedBayesian Nonparametric Estimation for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations

2 citations · 2 across the 1 of their papers we have counts for

collaborators

6 papers

stat.ME20202 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

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…

physics.soc-ph2020

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…

stat.CO2020

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…

stat.ME2019

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…

stat.ME2019

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…