David Hunter Professor, Penn State Department of Statistics

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 2020 semester, I am teaching DS 200, Introduction to Data Sciences; STAT 470, Problem Solving and Communication in Applied Statistics; and STAT 553, Asymptotic Tools.

In past semesters, I've taught or co-taught:

• 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, Identifying Bias and Falsehood (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 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 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 (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 (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 2017)
• STAT 597D, Statistical genetics and bioinformatics (spring 2001)

Papers

Papers about networks

• 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, in press.
• 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, 2:4.
• Hunter DR, Goodreau SM, Handcock MS (2013), ergm.userterms: A Template Package for Extending statnet, Journal of Statistical Software, 52(2).
• 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: 38-45.
• Hunter DR, Goodreau SM, and Handcock MS (2008), Goodness of fit of social network models, Journal of the American Statistical Association, 103: 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). 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). 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). 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). 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: 339-340.
• Hunter DR (2007), Curved exponential family models for social networks, Social Networks, 29: 216-230.
• Hunter DR and Handcock MS (2006), Inference in curved exponential family models for networks, Journal of Computational and Graphical Statistics, 15: 565-583.

Papers about mixture models

• Ranalli M, Lindsay BG, and Hunter DR (2019), A Classical Invariance Approach to the Normal Mixture Problem, Statistica Sinica, to appear.
• 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). 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: 505-526.
• Hunter DR, Wang S, and Hettmansperger TP (2007), Inference for mixtures of symmetric distributions, Annals of Statistics, 35: 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: 1617-1642.
• Hunter DR (2004), MM algorithms for generalized Bradley-Terry models, Annals of Statistics, 32: 386-408. (code)
• Hunter DR and Lange K (2004), A Tutorial on MM Algorithms, The American Statistician, 58: 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: 155-168. (code)
• Lange K, Hunter DR, Yang I (2000), Optimization transfer using surrogate objective functions, Journal of Computational and Graphical Statistics, 9: 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: 52-59.
• Hunter DR and Lange K (2000), Quantile regression via an MM algorithm, Journal of Computational and Graphical Statistics, 9: 60-77. (code)

Other papers and links

• DAB slides 1 DAB slides 2
• STAT 597 slides (from a 2016 talk) as well as some other slides.
• Slides for a talk I gave at IFCS 2019
• Slides for a talk I gave at SDSS 2019
• Lecture notes for course on asymptotics
• 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).
• 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.
• Links to R tutorials I have used during weeklong astrostatistics summer school workshops at Penn State (and once in Kavalur, India) are available here for these years: 2005   |   2006   |   2007   |   2010   |   2011
• Hunter DR (2005), Teaching computing in statistical theory courses, The American Statistician, 59: 327-333.
• Hunter DR, Richards DSP, and Rosenberger JL, editors (2011), Nonparametric Statistics and Mixture Models: A Festschrift in Honor of Thomas P. Hettmansperger, World Scientific, Singapore). Click below to see a larger picture of the cover:
  

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