David R Hunter

Professor of Statistics, Department Head

Research Summary

I work on statistical models for networks, mixture models, and certain optimization algorithms called MM algorithms. A full list of papers and related work, such as software, may be found at http://sites.stat.psu.edu/~dhunter/.

Huck Affiliations

Publication Tags

Exponential Family Social Networks Mixture Model Graph Model Random Graphs Network Model Conditional Independence Model Maximum Likelihood Likelihood Finite Mixture Models Bayesian Inference Invariance Epidemics Health Clustering Independent Component Analysis Assignment Simulation Genome Genes Maximum Likelihood Estimator Social Sciences Statistical Models Simulation Study

Most Recent Papers

SDSS 2020: Different, but (Mostly) Good

David Hunter, 2020, AmStat News on p. 1

A classical invariance approach to the normal mixture problem

Monia Ranalli, Bruce G. Lindsay, David R. Hunter, 2020, Statistica Sinica on p. 1235-1254

SDSS: Data Science and Statistics on the Pittsburgh Waterfront

David Hunter, Zhi Yang, Donna LaLonde, 2020, AmStat News on p. 1

Model-based clustering of time-evolving networks through temporal exponential-family random graph models

Kevin H. Lee, Lingzhou Xue, David R. Hunter, 2020, Journal of Multivariate Analysis

SDSS 2020 to Feature Refereed Submissions

David Hunter, 2019, AmStat News on p. 1

Clustering via finite nonparametric ICA mixture models

Xiaotian Zhu, David Russell Hunter, 2019, Advances in Data Analysis and Classification on p. 65-87

A statistician’s view of network modeling

David R. Hunter, 2019, on p. 23-41

Assignment of endogenous retrovirus integration sites using a mixture model

David R. Hunter, Le Bao, Mary Poss, 2017, Annals of Applied Statistics on p. 751-770

Theoretical grounding for estimation in conditional independence multivariate finite mixture models

Xiaotian Zhu, David R. Hunter, 2016, Journal of Nonparametric Statistics on p. 683-701

A pipeline for identifying integration sites of mobile elements in the genome using next-generation sequencing

Raunaq Malhotra, Daniel Elleder, Le Bao, David R. Hunter, Mary Poss, Raj Acharya, 2016, on p. 63-68

Most-Cited Papers

The dynamics of health behavior sentiments on a large online social network

Marcel Salathé, Duy Q. Vu, Shashank Khandelwal, David R. Hunter, 2013, EPJ Data Science on p. 1-12

Continuous-time regression models for longitudinal networks

Duy Q. Vu, Arthur U. Asuncion, David R. Hunter, Padhraic Smyth, 2011,

Computational statistical methods for social network models

David R. Hunter, Pavel N. Krivitsky, Michael Schweinberger, 2012, Journal of Computational and Graphical Statistics on p. 856-882

Statistical inference to advance network models in epidemiology

David Welch, Shweta Bansal, David R. Hunter, 2011, Epidemics on p. 38-45

Dynamic egocentric models for citation networks

Duy Q. Vu, Arthur U. Asuncion, David R. Hunter, Padhraic Smyth, 2011, on p. 857-864

Semiparametric mixtures of regressions

David R. Hunter, Derek S. Young, 2012, Journal of Nonparametric Statistics on p. 19-38

Maximum smoothed likelihood for multivariate mixtures

M. Levine, D. R. Hunter, D. Chauveau, 2011, Biometrika on p. 403-416

Bayesian Inference for Contact Networks Given Epidemic Data

Chris Groendyke, David Welch, David R. Hunter, 2011, Scandinavian Journal of Statistics on p. 600-616

A Network-based Analysis of the 1861 Hagelloch Measles Data

Chris Groendyke, David Welch, David R. Hunter, 2012, Biometrics on p. 755-765

Improving simulation-based algorithms for fitting ERGMs

Ruth M. Hummel, David R. Hunter, Mark S. Handcock, 2012, Journal of Computational and Graphical Statistics on p. 920-939