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 Random Graphs Graph Model Network Model Mixture Model Finite Mixture Models Model Conditional Independence Clustering Social Networks Approximation Simulation Template Invariance Model Based Clustering Genes Semiparametric Estimation Random Effects Independent Component Analysis Health Assignment Regression Genome Modeling Maximum Likelihood Estimator

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 R. 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

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

Semiparametric mixtures of regressions

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

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

Model-based clustering of large networks

Duy Q. Vu, David R. Hunter, Michael Schweinberger, 2013, Annals of Applied Statistics on p. 1010-1039

Ergm.userterms: A template package for extending statnet

David R. Hunter, Steven M. Goodreau, Mark S. Handcock, 2013, Journal of Statistical Software on p. 1-25

Semi-parametric estimation for conditional independence multivariate finite mixture models

Didier Chauveau, David R. Hunter, Michael Levine, 2015, Statistics Surveys

Random effects regression mixtures for analyzing infant habituation

Derek S. Young, David R. Hunter, 2015, Journal of Applied Statistics on p. 1421-1441

An Approximation Method for Improving Dynamic Network Model Fitting

Nicole Bohme Carnegie, Pavel N. Krivitsky, David R. Hunter, Steven M. Goodreau, 2015, Journal of Computational and Graphical Statistics on p. 502-519