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
Most Recent Publications
Improving ERGM starting values using simulated annealing
Christian S. Schmid, David R. Hunter, 2024, Social Networks on p. 209-214
A DYNAMIC ADDITIVE AND MULTIPLICATIVE EFFECTS NETWORK MODEL WITH APPLICATION TO THE UNITED NATIONS VOTING BEHAVIORS
Bomin Kim, Xiaoyue Niu, David Hunter, Xun Cao, 2023, Annals of Applied Statistics on p. 3283-3299
Computing Pseudolikelihood Estimators for Exponential-Family Random Graph Models
Christian S. Schmid, David R. Hunter, 2023, Journal of Data Science on p. 295-309
Unsupervised clustering using nonparametric finite mixture models
David Hunter, 2023, Wiley Interdisciplinary Reviews: Computational Statistics on p. 11
ergm 4: New Features for Analyzing Exponential-Family Random Graph Models
Pavel N. Krivitsky, David Hunter, Martina Morris, Chad Klumb, 2023, Journal of Statistical Software on p. 1-44
Likelihood-based inference for exponential-family random graph models via linear programming
Pavel N. Krivitsky, Alina R. Kuvelkar, David R. Hunter, 2023, Electronic Journal of Statistics on p. 3337-3356
Computing Pseudolikelihood Estimators for Exponential-Family Random Graph Models
Christian Schmid, David Hunter, 2023, Journal of Data Science on p. 295-309
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
Most-Cited Papers
ergm 4: New Features for Analyzing Exponential-Family Random Graph Models
Pavel N. Krivitsky, David Hunter, Martina Morris, Chad Klumb, 2023, Journal of Statistical Software on p. 1-44
Semi-parametric estimation for conditional independence multivariate finite mixture models
Didier Chauveau, David R. Hunter, Michael Levine, 2015, Statistics Surveys
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
Clustering via finite nonparametric ICA mixture models
Xiaotian Zhu, David R. Hunter, 2019, Advances in Data Analysis and Classification on p. 65-87
Random effects regression mixtures for analyzing infant habituation
Derek S. Young, David R. Hunter, 2015, Journal of Applied Statistics on p. 1421-1441
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
RASE: Modeling cumulative disadvantage due to marginalized group status in academia
Sarah Shandera, Jes L. Matsick, David R. Hunter, Louis Leblond, 2021, PLoS One
Computing Pseudolikelihood Estimators for Exponential-Family Random Graph Models
Christian S. Schmid, David R. Hunter, 2023, Journal of Data Science on p. 295-309
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
A DYNAMIC ADDITIVE AND MULTIPLICATIVE EFFECTS NETWORK MODEL WITH APPLICATION TO THE UNITED NATIONS VOTING BEHAVIORS
Bomin Kim, Xiaoyue Niu, David Hunter, Xun Cao, 2023, Annals of Applied Statistics on p. 3283-3299