Scholars@Duke

• Background
• 

  Education, Training, & Certifications

  • Ph.D., Purdue University 2006
• 

  Duke Appointment History

  • Co-Director of Graduate Studies in the Department of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2013 - 2016
  • Assistant Professor of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2009 - 2016
• Recognition
• 

  Awards & Honors

  • Leonard J. Savage Dissertation Award (Theory & Methods). ISBA, ASA-SBSS and NBER/NSF Seminars on Bayesian Inference in Econometrics and Statistics. 2006
• Research
• 

  Selected Grants

  • Spatial Information Codes awarded by National Institutes of Health 2017 - 2022
  • Information in Limited-Capacity Neural Codes awarded by National Institutes of Health 2017 - 2019
  • Understanding Regression Heterogeneity Through Joint Estimation of Conditional Quantiles awarded by  National Science Foundation 2016 - 2019
  • Bayesian Methods for Assessing Gene by Environment Interactions awarded by National Institutes of Health 2009 - 2015
• Publications & Artistic Works
• 

  Selected Publications

  • Book Sections

    • Ghosh, JK, and Tokdar, ST. "Convergence and consistency of Newton’s algorithm for estimating mixing distribution." In Frontiers in Statistics: Dedicated to Peter John Bickel in Honor of his 65th Birthday, 429-443. January 1, 2006.  Full Text

  • Journal Articles

    • Burris, K, Vittetoe, K, Ramger, B, Suresh, S, Tokdar, ST, Reiter, JP, and Appelbaum, LG. "Sensorimotor abilities predict on-field performance in professional baseball." Scientific reports 8, no. 1 (January 8, 2018): 116-.  Full Text
    • Klemish, D, Ramger, B, Vittetoe, K, Reiter, JP, Tokdar, ST, and Appelbaum, LG. "Visual abilities distinguish pitchers from hitters in professional baseball." Journal of sports sciences 36, no. 2 (January 2018): 171-179.  Full Text
    • Montagna, S, and Tokdar, ST. "Computer emulation with non-stationary Gaussian processes." SIAM/ASA Journal of Uncertainty Quantification 4 (2016): 26-47.  Link to Item
    • Yang, Y, and Tokdar, ST. "Minimax-optimal nonparametric regression in high dimensions." Annals of Statistics 43, no. 2 (2015): 652-674.  Full Text
    • Pati, D, Dunson, DB, and Tokdar, ST. "Posterior consistency in conditional distribution estimation." Journal of Multivariate Analysis 116 (2013): 456-472.  Full Text
    • Shen, W, Tokdar, ST, and Ghosal, S. "Adaptive Bayesian multivariate density estimation with Dirichlet mixtures." Biometrika 100, no. 3 (2013): 623-640.  Full Text
    • Montagna, S, Tokdar, ST, Neelon, B, and Dunson, DB. "Bayesian latent factor regression for functional and longitudinal data." Biometrics 68, no. 4 (December 2012): 1064-1073.  Full Text  Link to Item
    • Martin, R, and Tokdar, ST. "A nonparametric empirical Bayes framework for large-scale multiple testing." Biostatistics 13, no. 3 (2012): 427-439.  Full Text
    • Tokdar, ST, and Kadaney, JB. "Simultaneous linear quantile regression: A semiparametric bayesian approach." Bayesian Analysis 7, no. 1 (2012): 51-72.  Full Text
    • Bisi, A, Dada, M, and Tokdar, S. "A censored-data multiperiod inventory problem with newsvendor demand distributions." Manufacturing and Service Operations Management 13, no. 4 (2011): 525-533.  Full Text
    • Martin, R, and Tokdar, ST. "Semiparametric inference in mixture models with predictive recursion marginal likelihood." Biometrika 98, no. 3 (2011): 567-582.  Full Text
    • Tokdar, ST, Grossmann, I, Kadane, JB, Charest, A-S, and Small, MJ. "Impact of beliefs about atlantic tropical cyclone detection on conclusions about trends in tropical cyclone numbers." Bayesian Analysis 6, no. 4 (2011): 547-572.  Full Text
    • Tokdar, S, Xi, P, Kelly, RC, and Kass, RE. "Detection of bursts in extracellular spike trains using hidden semi-Markov point process models." J Comput Neurosci 29, no. 1-2 (August 2010): 203-212.  Full Text  Link to Item
    • Tokdar, ST, Zhu, YM, and Ghosh, JK. "Bayesian density regression with logistic Gaussian process and subspace projection." Bayesian Analysis 5, no. 2 (2010): 319-344.  Full Text
    • Tokdar, ST, and Kass, RE. "Importance sampling: A review." Wiley Interdisciplinary Reviews: Computational Statistics 2, no. 1 (2010): 54-60.  Full Text
    • Martin, R, and Tokdar, ST. "Asymptotic properties of predictive recursion: Robustness and rate of convergence." Electronic Journal of Statistics 3, no. 0 (2009): 1455-1472.  Full Text
    • Tokdar, ST, Ryan, M, and Ghosh, JK. "Consistency of a recursive estimate of mixingdistributions." Annals of Statistics 37, no. 5 A (2009): 2502-2522.  Full Text
    • Bogdan, M, Ghosh, JK, Ochman, A, and Tokdar, ST. "On the empirical bayes approach to the problem of multiple testing." Quality and Reliability Engineering International 23, no. 6 (2007): 727-739.  Full Text
    • Tokdar, ST, and Ghosh, JK. "Posterior consistency of logistic Gaussian process priors in density estimation." Journal of Statistical Planning and Inference 137, no. 1 (2007): 34-42.  Full Text
    • Tokdar, ST. "Towards a faster implementation of density estimation with logistic gaussian process priors." Journal of Computational and Graphical Statistics 16, no. 3 (2007): 633-655.  Full Text
    • Tokdar, ST. "Posterior consistency of dirichlet location-scale mixture of normals in density estimation and regression." Sankhya: The Indian Journal of Statistics 68, no. 1 (2006): 90-110.
    • Banerjee, A, Dunson, D, and Tokdar, S. "Efficient Gaussian Process Regression for Large Data Sets."  Open Access Copy  Link to Item
    • Bogdan, M, Ghosh, JK, and Tokdar, ST. "A comparison of the Benjamini-Hochberg procedure with some Bayesian rules for multiple testing." IMS Collections 1, no. 2: 1-230.  Full Text  Link to Item
    • Glynn, C, Tokdar, ST, Banks, DL, and Howard, B. "Bayesian Analysis of Dynamic Linear Topic Models."  Link to Item
    • Yang, Y, and Tokdar, S. "Joint estimation of quantile planes over arbitrary predictor spaces." Journal of the American Statistical Association Forthcoming.  Link to Item
• Teaching & Mentoring
• 

  Recent Courses

  • MATH 790-71: Current Research in Applied Mathematics 2018
  • STA 701S: Readings in Statistical Science 2018
  • STA 941: Bayesian Nonparametric Models and Methods 2018
  • STA 961: Stochastic Processes 2018
  • STA 581: ProSeminar: Becoming a Statistical Scientist 2016
  • STA 732: Statistical Inference 2016

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