David R Hunter
Professor of Statistics, Department Head
- He/Him
- dhunter@stat.psu.edu
- 814-863-0979
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 Clustering Conditional Independence Finite Mixture Models Independent Component Analysis Mixture Model Model Model Based Clustering Network Model Random Effects Health Semiparametric Estimation Template Invariance Modeling Simulation Study Dissolution Approximation Statistics Trajectory Dynamic Networks Framework Objective FunctionMost Recent Publications
RASE: Modeling cumulative disadvantage due to marginalized group status in academia
Sarah Shandera, Jes L. Matsick, David R. Hunter, Louis Leblond, 2021, PLoS One
Alternating Minimization Algorithms
David Hunter, 2021, on p. 1-10
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 on p. 104540
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
An expansive view of EM algorithms
David Hunter, Prabhani Kuruppumullage Don, Prabhani Don, B Lindsay, 2019, on p. 41--54
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
Model-based clustering of large networks
Duy 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
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 on p. 104540
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
Computational and statistical analyses of insertional polymorphic endogenous retroviruses in a non-model organism
Le Bao, Daniel Elleder, Raunaq Malhotra, Michael DeGiorgio, Theodora Maravegias, Lindsay Horvath, Laura Carrel, Colin Gillin, Tomáš Hron, Helena Fábryová, David R. Hunter, Mary Poss, 2014, Computation on p. 221-245
Clustering via finite nonparametric ICA mixture models
Xiaotian Zhu, David R. Hunter, 2019, Advances in Data Analysis and Classification on p. 65-87
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