I received my Ph.D. in 1999 from the
Department of Statistics
at the
University of Michigan
in
Ann Arbor, Michigan.
Teaching
In the SP 2023 semester, I am teaching
STAT 553, Asymptotic Tools and
STAT 590, Colloquium and Perspectives on Statistics.
In past semesters, I've taught or co-taught:
- DS 200, Introduction to Data Sciences
(spring 2020 and spring 2022)
- FRNSC 597A, Applied Forensic Science Statistics(fall 2014)
- PSU 016, Statistics first-year seminar
(fall 2011 and
fall 2010 and
fall 2009 and
fall 2008 and
fall 2006 and
fall 2005)
- SC 205N, BS: Identifying Bias and Falsehood (fall 2021 and fall 2018, co-taught with Paula Droege)
- STAT 100, Statistical concepts and reasoning
(fall 2015 and
fall 2013 and
fall 2012 and
fall 2008 and
spring 2004 and
spring 2005 and
fall 2005)
- STAT 200, Elementary Statistics
(fall 2021 and fall 2016)
- STAT 200H, Honors Elementary Statistics
(fall 2002 and fall 1999)
- STAT 220, Basic Statistics for Quantitative Students
(spring 2006)
- STAT 250, Introduction to Biostatistics (fall 2022 and fall 2017)
- STAT 250H, Honors Biostatistics
(spring 2003 and spring 2002)
- STAT 401, Experimental Methods (spring 2004 and
spring 2000)
- STAT 414, Introduction to Probability Theory (fall 2010 and
fall 2009 and
spring 2009)
- STAT 460,
Intermediate Applied Statistics
(fall 2001 and spring 2000)
- STAT 470, Problem Solving and Communication in Applied Statistics (spring 2020 and fall 2018)
- STAT 514, Theory of Statistics II (fall 2014)
- STAT 515, Stochastic Processes I (spring 2012)
- STAT 525, Survival Analysis I (spring 2011)
- STAT 553, Asymptotic Tools
(spring 2020 and
fall 2011 and
fall 2006 and
fall 2004 and
fall 2003 and
fall 2002 and
fall 2001
and fall 2000)
Course lecture notes
- STAT 590, Colloquium and Perspectives on Statistics
(spring 2022 and spring 2017)
- STAT 597D,
Statistical genetics and bioinformatics
(spring 2001, co-taught with Francesca Chiaromonte)
Papers
The papers below are classified into several approximate (non-mutually-exclusive) categories.
In some cases, related
computer code is available online.
Some of the articles can't be posted on this website due to copyright issues.
Papers about networks
-
Krivitsky PN, Hunter DR, Morris M, Klumb C (2022),
ergm 4: New features,
ArXiv Preprint, arXiv:2106.04997.
-
Krivitsky PN, Hunter DR, Morris M, Klumb C (2022),
ergm 4: Computational Improvements,
ArXiv Preprint, arXiv:2203.08198.
-
Krivitsky PN, Kuvelkar AR, Hunter DR (2022),
Likelihood-based Inference for Exponential-Family Random Graph Models via Linear
Programming,
ArXiv Preprint, arXiv:2202.03572.
-
Schmid C, Hunter DR (2020),
Improving ERGM Starting Values Using Simulated Annealing,
ArXiv Preprint, arXiv:2009.01202.
- Lee KH, Xue L, and Hunter DR (2020),
Model-based
clustering of time-evolving networks through temporal exponential-family random graph models,
Journal of Multivariate Analysis,
175 (104540): 1-17.
- Carnegie NB, Krivitsky PN, Hunter DR, Goodreau SM (2015),
An
approximation method for improving dynamic network model fitting,
Journal
of Computational and Graphical Statistics,
24 (2): 502-519.
- Vu DQ, Hunter DR, and Schweinberger M (2013),
Model-Based Clustering of Large Networks,
Annals of Applied Statistics,
7 (2): 1010-1039.
(code)
- Salathe M, Vu DQ, Khandelwal S, Hunter DR (2013),
The Dynamics
of Health Behavior Sentiments on a Large Online Social Network,
EPJ Data Science,
2 (1): 1-12.
- Hunter DR, Goodreau SM, Handcock MS (2013),
ergm.userterms: A Template Package for Extending statnet,
Journal of Statistical Software,
52 (2): 1-25.
-
Hunter DR, Krivitsky PN, and Schweinberger M (2012),
Computational
Statistical Methods for Social Network Analysis,
Journal of Computational and Graphical Statistics,
21 (4): 856-882.
- Hummel RM, Hunter DR, Handcock MS (2012),
Improving Simulation-Based Algorithms for Fitting ERGMs,
Journal
of Computational and Graphical Statistics,
21 (4): 920-939.
Here is the supplemental code.
- Groendyke C, Welch D, Hunter DR (2012),
A
Network-Based Analysis of the 1861 Hagelloch Measles Data,
Biometrics, 68 (3): 755-765.
- Vu DQ, Asuncion AU, Hunter DR, Smyth P (2011), Continuous-Time
Regression Models for Longitudinal Networks,
Advances in Neural Information
Processing Systems 24 (NIPS 2011), 2492-2500.
- Groendyke C, Welch D, Hunter DR (2011),
Bayesian Inference for Contact Networks Given Epidemic Data,
Scandanavian Journal of Statistics, 38 (3): 600-616.
- Vu DQ, Asuncion AU, Hunter DR, Smyth P (2011), Dynamic Egocentric
Models for Citation Networks,
Proceedings of the 28th International Conference on Machine Learning (ICML 2011), 857-864.
(code)
- Welch D, Bansal S, Hunter DR (2011),
Statistical inference to advance network models in epidemiology,
Epidemics, 3 (1): 38-45.
- Hunter DR, Goodreau SM, and Handcock MS (2008),
Goodness of fit of social network models,
Journal
of the American Statistical Association,
103 (481): 248-258.
- Handcock MS, Hunter DR, Butts CT, Goodreau SM, and Morris M (2008),
statnet: Software Tools for the Representation, Visualization, Analysis
and Simulation of Network Data,
Journal of Statistical Software,
24 (1): 1-11. URL http://www.jstatsoft.org/v24/i01
- Hunter DR, Handcock MS, Butts CT, Goodreau SM, and Morris M (2008),
ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks,
Journal of Statistical Software,
24 (3): 1-29. URL http://www.jstatsoft.org/v24/i03
- Morris M, Handcock MS, and Hunter DR (2008),
Specification of Exponential-Family Random Graph Models: Terms and Computational
Aspects,
Journal of Statistical Software,
24 (4): 1-24. URL http://www.jstatsoft.org/v24/i04
- Goodreau SM, Handcock MS, Hunter DR, Butts CT, and Morris M (2008),
A statnet Tutorial,
Journal of Statistical Software,
24 (9): 1-26. URL http://www.jstatsoft.org/v24/i09
- Hunter DR (2007),
Comment on "Model-Based Clustering for Social Networks"
by Handcock MS, Raftery AE, and Tantrum JM,
Journal of the Royal Statistical Society, Series A,
170 (2): 339-340.
- Hunter DR (2007), Curved exponential family
models for social networks,
Social Networks, 29 (2): 216-230.
- Hunter DR and Handcock MS (2006),
Inference in curved exponential family
models for networks,
Journal
of Computational and Graphical Statistics, 15 (3): 565-583.
Papers about mixture models
- Ranalli M, Lindsay BG, and Hunter DR (2020),
A Classical
Invariance Approach to the Normal Mixture Problem,
Statistica Sinica,
30 (3): 1354-1254.
- Lee KH, Xue L, and Hunter DR (2020),
Model-based
clustering of time-evolving networks through temporal exponential-family random graph models,
Journal of Multivariate Analysis,
175 (104540): 1-17.
- Zhu X and Hunter DR (2019),
Clustering Via Finite Nonparametric ICA Mixture Models,
Advances
in Data Analysis and Classification, 13 (1): 65-87.
- Hunter DR, Bao L, and Poss M (2017), Assignment of
Endogenous Retrovirus Integration Sites Using a Mixture Model,
Annals of Applied Statistics, 11 (2): 751-770.
- Zhu X and Hunter DR (2016), Theoretical
Grounding for Estimation in Conditional Independence Multivariate Finite Mixture Models,
Journal of Nonparametric Statistics,
28 (4): 683-701.
- Young DS and Hunter DR (2015), Random
Effects Regression Mixtures for Analyzing Infant Habituation,
Journal of Applied Statistics,
42 (7): 1421-1441.
- Chauveau D, Hunter DR, Levine M (2015), Semi-Parametric
Estimation for Conditional
Independence Multivariate Finite Mixture Models,
Statistics Surveys,
9: 1-31.
- Vu DQ, Hunter DR, and Schweinberger M (2013),
Model-Based Clustering of Large Networks,
Annals of Applied Statistics,
7 (2): 1010-1039.
(code)
- Hunter DR and Young DS (2012),
Semiparametric Mixtures of Regressions,
Journal of Nonparametric Statistics,
24 (1): 19-38.
- Levine M, Hunter DR, Chauveau D (2011), Maximum Smoothed Likelihood
for Multivariate Mixtures,
Biometrika,
98 (2): 403-416.
- Benaglia T, Chauveau D, Hunter DR (2011),
Bandwidth
Selection in an EM-like Algorithm for Nonparametric
Multivariate Mixtures,
in DR Hunter, DSP Richards, and JL Rosenberger (eds.),
Nonparametric Statistics and Mixture
Models: A Festschrift in Honor of Thomas P. Hettmansperger,
(World Scientific, Singapore), pp. 15-27.
- Young DS, Hunter DR (2010),
Mixtures of Regressions with Predictor-Dependent Mixing Proportions,
Computational Statistics and Data Analysis,
54 (10): 2253-2266.
- Benaglia T, Chauveau D, Hunter DR, and Young DS (2009),
mixtools: An R Package for Analyzing Finite Mixture Models,
Journal of Statistical Software,
32 (6): 1-29. URL http://www.jstatsoft.org/v32/i06.
- Benaglia T, Chauveau D, and Hunter DR (2009),
An EM-like algorithm for semi- and non-parametric estimation in
multivariate mixtures,
Journal
of Computational and Graphical Statistics,
18 (2): 505-526.
- Hunter DR, Wang S, and Hettmansperger TP (2007),
Inference for mixtures of symmetric
distributions,
Annals of Statistics,
35 (1): 224-251.
(code)
Papers about or involving MM algorithms
- Hunter DR, Kuruppumullage Don P, and Lindsay BG (2019),
An
Expansive View of EM Algorithms,
in Handbook of Mixture Analysis,
S Fruehwirth-Schnatter, G Celeux, and CP Robert, editors.
- Hunter DR (2014),
Invited discussion of "A Brief History of Modern Optimization for Statisticians"
by Lange, Chi, and Zhou,
International Statistical Review, 82 (1): 76-79.
- Chauveau D and Hunter DR (2013),
ECM
and MM algorithms for normal mixtures with constrained parameters,
hal-00625285, version 2.
- Vu DQ, Hunter DR, and Schweinberger M (2013),
Model-Based Clustering of Large Networks,
Annals of Applied Statistics,
7 (2): 1010-1039.
(code)
- Levine M, Hunter DR, Chauveau D (2011), Maximum Smoothed Likelihood
for Multivariate Mixtures,
Biometrika,
98 (2): 403-416.
- Hunter DR and Li R (2005),
Variable
selection using MM algorithms,
Annals of Statistics,
33 (4): 1617-1642.
- Hunter DR (2004),
MM algorithms for generalized Bradley-Terry
models, Annals of Statistics, 32 (1): 386-408.
(code)
- Hunter DR and Lange K (2004),
A Tutorial on MM Algorithms,
The American
Statistician, 58 (1): 30-37.
- Hunter DR (2003),
On the geometry of EM algorithms,
Penn State Department of Statistics Technical Report 0303.
- Hunter DR and Lange K (2002),
Computing estimates in the proportional odds model,
Annals
of the Institute of
Statistical Mathematics,
54 (1): 155-168.
(code)
- Lange K, Hunter DR, Yang I (2000),
Optimization transfer using surrogate objective
functions, Journal
of Computational and Graphical
Statistics, 9 (1): 1-20.
- Hunter DR and Lange K (2000), Rejoinder
to discussion of
"Optimization transfer using surrogate objective functions",
Journal
of Computational and Graphical Statistics,
9 (1): 52-59.
- Hunter DR and Lange K (2000),
Quantile regression via an MM algorithm,
Journal
of Computational and Graphical Statistics,
9 (1): 60-77.
(code)
Other papers
-
Malhotra DE, Bao L, Hunter DR, Poss M, and Acharya R (2016),
A Pipeline for Identifying Integration Sites of Mobile Elements in the Genome Using
Next-Generation Sequencing,
Proceedings of the 8th International Conference on Bioinformatics and Computational
Biology (BICOB 2016), 63-68.
-
Bao L, Elleder D, Malhotra R, DeGiorgio M, Maravegias T, Horvath L,
Carrel L, Gillin C, Hron T, Fabryova H, Hunter DR, and
Poss M (2014),
Computational
and statistical analyses of insertional polymorphic
endogenous retroviruses in a non-model organism,
Computation,
2 (4), 221-245.
- Hunter DR (2005),
Teaching computing in statistical theory
courses,
The American
Statistician, 59: 327-333.
-
Shandera S, Matsick, JL, Hunter DR, and Leblond L (2021),
RASE: Modeling
Cumulative Disadvantage Due to Marginalized Group Status in Academia,
PLOS One,
16 (12), e0260567.
Miscellaneous links
