Selected Bibliography for Nicholas Polson

Robert Law, Jr. Professor of Econometrics and Statistics

Home page of Nicholas Polson

Nicholas Polson author profile at Scopus

Published Works

"Chess Ai: Competing Paradigms for Machine Intelligence." Shiva Maharaj, Nick Polson and Alex Turk; Entropy, 2022, 24(4), pp. 550.

"Gambits: Theory and Evidence." Shiva Maharaj, Nick Polson and Christian Turk; Applied Stochastic Models in Business and Industry, 2022, 38(4), pp. 572-89.

"The Horseshoe-Like Regularization for Feature Subset Selection." Anindya Bhadra, Jyotishka Datta, Nicholas G. Polson and Brandon T. Willard; Sankhya B, 2021, 83(1), pp. 185-214.

"Horseshoe Regularisation for Machine Learning in Complex and Deep Models1." Anindya Bhadra, Jyotishka Datta, Yunfan Li and Nicholas Polson; International Statistical Review, 2020, 88(2), pp. 302-20.

"Short Communication: Deep Fundamental Factor Models." Matthew Dixon and Nick Polson; SIAM Journal on Financial Mathematics, 2020, 11(3), pp. SC26-SC37.

"Global-Local Mixtures: A Unifying Framework." Anindya Bhadra, Jyotishka Datta, Nicholas G. Polson and Brandon T. Willard; Sankhya A, 2020, 82(2), pp. 426-47.

"A Family of Multivariate Non-Gaussian Time Series Models." Tevfik Aktekin, Nicholas G. Polson and Refik Soyer; Journal of Time Series Analysis, 2020, 41(5), pp. 691-721.

"Deep Learning: Computational Aspects." Nicholas Polson and Vadim Sokolov; WIREs Computational Statistics, 2020, 12(5), pp. e1500.

"Regularizing Bayesian Predictive Regressions." Guanhao Feng and Nicholas Polson; Journal of Asset Management, 2020, 21(7), pp. 591-608.

"Bayesian L0-Regularized Least Squares." Nicholas G. Polson and Lei Sun; Applied Stochastic Models in Business and Industry, 2019, 35(3), pp. 717-31.

"Deep Learning for Spatio-Temporal Modeling: Dynamic Traffic Flows and High Frequency Trading." Matthew F. Dixon, Nicholas G. Polson and Vadim O. Sokolov; Applied Stochastic Models in Business and Industry, 2019, 35(3), pp. 788-807.

"Bayesian Regularization: From Tikhonov to Horseshoe." Nicholas G. Polson and Vadim Sokolov; WIREs Computational Statistics, 2019, 11(4), pp. e1463.

"Lasso Meets Horseshoe: A Survey." Anindya Bhadra, Jyotishka Datta, Nicholas G. Polson and Brandon Willard; Statistical Science, 2019, 34(3), pp. 405-27, 23.

"Bayesian Hypothesis Testing: Redux." Hedibert F. Lopes and Nicholas G. Polson; Brazilian Journal of Probability and Statistics, 2019, 33(4), pp. 745-55, 11.

"Posterior Concentration for Sparse Deep Learning," Nicholas G. Polson and Veronika Ročková, Advances in Neural Information Processing Systems Editor, Curran Associates, Inc., 2018 of Conference, pp. Pages.

"From Least Squares to Signal Processing and Particle Filtering." Nozer D. Singpurwalla, Nicholas G. Polson and Refik Soyer; Technometrics, 2018, 60(2), pp. 146-60.

"Sequential Bayesian Analysis of Multivariate Count Data." Tevfik Aktekin, Nick Polson and Refik Soyer; Bayesian Analysis, 2018, 13(2), pp. 385-409, 25.

"Sequential Bayesian Learning for Stochastic Volatility with Variance-Gamma Jumps in Returns." Samir P. Warty, Hedibert F. Lopes and Nicholas G. Polson; Applied Stochastic Models in Business and Industry, 2018, 34(4), pp. 460-79.

"Rejoinder to “Sequential Bayesian Learning for Stochastic Volatility with Variance-Gamma Jumps in Returns” Reply to the Discussions by Nalini Ravishanker and Refik Soyer." Samir P. Warty, Hedibert F. Lopes and Nicholas G. Polson; Applied Stochastic Models in Business and Industry, 2018, 34(4), pp. 484-85.

"Statistical Sparsity." Peter McCullagh and Nicholas G. Polson; Biometrika, 2018, 105(4), pp. 797-814.

"Bayesian Particle Tracking of Traffic Flows." Nicholas G. Polson and Vadim Sokolov; IEEE Transactions on Intelligent Transportation Systems, 2018, 19(2), pp. 345-56.

"A Deconvolution Path for Mixtures." Oscar-Hernan Madrid-Padilla, Nicholas G. Polson and James Scott; Electronic Journal of Statistics, 2018, 12(1), pp. 1717-51.

"Deep Learning for Finance: Deep Portfolios." James B. Heaton, Nicholas G. Polson and Jan H. Witte; Applied Stochastic Models in Business and Industry, 2017, 33(1), pp. 3-12.

"Rejoinder to 'Deep Learning for Finance: Deep Portfolios'." James B. Heaton, Nicholas Polson and Jan H. Witte; Applied Stochastic Models in Business and Industry, 2017, 33(1), pp. 19-21.

"Deep Learning: A Bayesian Perspective." Nicholas G. Polson and Vadim Sokolov; Bayesian Analysis, 2017, 12(4), pp. 1275-304, 30.

"Augmented Probability Simulation for Accelerated Life Test Design." Nicholas G. Polson and Refik Soyer; Applied Stochastic Models in Business and Industry, 2017, 33(3), pp. 322-32.

"The Horseshoe+ Estimator of Ultra-Sparse Signals." Anindya Bhadra, Jyotishka Datta, Nicholas G. Polson and Brandon Willard; Bayesian Analysis, 2017, 12(4), pp. 1105-31, 27.

"Deep Learning for Short-Term Traffic Flow Prediction." Nicholas G. Polson and Vadim O. Sokolov; Transportation Research Part C: Emerging Technologies, 2017, 79, pp. 1-17.

"Why Indexing Works." James B. Heaton, Nicholas G. Polson and Jan H. Witte; Applied Stochastic Models in Business and Industry, 2017, 33(6), pp. 690-93.

"Augmented Nested Sampling for Stochastic Programs with Recourse and Endogenous Uncertainty." Tahir Ekin, Nicholas G. Polson and Refik Soyer; Naval Research Logistics (NRL), 2017, 64(8), pp. 613-27.

"Mixtures, Envelopes and Hierarchical Duality." Nicholas G. Polson and James G. Scott; Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2016, 78(4), pp. 701-27.

"Particle Learning for Fat-Tailed Distributions." Hedibert F. Lopes and Nicholas G. Polson; Econometric Reviews, 2016, 35(8-10), pp. 1666-91.

"The Market for English Premier League (Epl) Odds." Guanhao Feng, Nicholas Polson and Jianeng Xu; Journal of Quantitative Analysis in Sports, 2016, 12(4), pp. 167-78.

"Proximal Algorithms in Statistics and Machine Learning." Nicholas G. Polson, James G. Scott and Brandon T. Willard; Statistical Science, 2015, 30(4), pp. 559-81, 23.

"Bayesian Estimation of Nonlinear Equilibrium Models with Random Coefficients." V. Brian Viard, Anne Gron and Nicholas G. Polson; Applied Stochastic Models in Business and Industry, 2015, 31(4), pp. 435-56.

"The Implied Volatility of a Sports Game." Nicholas G. Polson and Hal S. Stern; Journal of Quantitative Analysis in Sports, 2015, 11(3), pp. 145-53.

"Bayesian Analysis of Traffic Flow on Interstate I-55: The Lwr Model." Nicholas Polson and Vadim Sokolov; The Annals of Applied Statistics, 2015, 9(4), pp. 1864-88, 25.

"Augmented Markov Chain Monte Carlo Simulation for Two-Stage Stochastic Programs with Recourse." Tahir Ekin, Nicholas G. Polson and Refik Soyer; Decision Analysis, 2014, 11(4), pp. 250-64.

"The Bayesian Bridge." Nicholas G. Polson, James G. Scott and Jesse Windle; Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2014, 76(4), pp. 713-33.

"Analyzing Risky Choices: Q-Learning for Deal-No-Deal." Laszlo Korsos and Nicholas G. Polson; Applied Stochastic Models in Business and Industry, 2014, 30(3), pp. 258-70.

"Sequential Learning, Predictability, and Optimal Portfolio Returns." Michael Johannes, Arthur Korteweg and Nicholas Polson; The Journal of Finance, 2014, 69(2), pp. 611-44.

"Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables." Nicholas G. Polson, James G. Scott and Jesse Windle; Journal of the American Statistical Association, 2013, 108(504), pp. 1339-49.

"Data Augmentation for Non-Gaussian Regression Models Using Variance-Mean Mixtures." Nicholas G. Polson and J. G. Scott; Biometrika, 2013, 100(2), pp. 459-71.

"Bayesian Instrumental Variables: Priors and Likelihoods." Hedibert F. Lopes and Nicholas G. Polson; Econometric Reviews, 2013, 33(1-4), pp. 100-21.

"Optimal Portfolio Choice and Stochastic Volatility." Anne Gron, Bjørn N. Jørgensen and Nicholas G. Polson; Applied Stochastic Models in Business and Industry, 2012, 28(1), pp. 1-15.

"Bayesian Statistics with a Smile: A Resampling-Sampling Perspective." Hedibert F. Lopes, Nicholas G. Polson and Carlos M. Carvalho; Brazilian Journal of Probability and Statistics, 2012, 26(4), pp. 358-71.

"Tracking Epidemics with Google Flu Trends Data and a State-Space Seir Model." Vanja Dukic, Hedibert F. Lopes and Nicholas G. Polson; Journal of the American Statistical Association, 2012, 107(500), pp. 1410-26.

"On the Half-Cauchy Prior for a Global Scale Parameter." Nicholas G. Polson and James G. Scott; Bayesian Analysis, 2012, 7(4), pp. 887-902.

"Simulation-Based Regularized Logistic Regression." Robert B. Gramacy and Nicholas G. Polson; Bayesian Analysis, 2012, 7(3), pp. 567-90.

"Local Shrinkage Rules, Lévy Processes and Regularized Regression." Nicholas G. Polson and James G. Scott; Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2012, 74(2), pp. 287-311.

"Rejoinder: "Data Augmentation for Support Vector Machines"." Nicholas G. Polson and Steven L. Scott; Bayesian Analysis, 2011, 6(1), pp. 43-47.

"Discussion on ‘Adversarial Risk Analysis: Borel Games’." Nicholas Polson; Applied Stochastic Models in Business and Industry, 2011, 27(2), pp. 89-91.

"A Simulation-Based Approach to Stochastic Dynamic Programming." Nicholas G. Polson and Morten Sorensen; Applied Stochastic Models in Business and Industry, 2011, 27(2), pp. 151-63.

"Predictive Macro-Finance with Dynamic Partition Models." Daniel Zantedeschi, Paul Damien and Nicholas G. Polson; Journal of the American Statistical Association, 2011, 106(494), pp. 427-39.

"Data Augmentation for Support Vector Machines." Nicholas G. Polson and Steven L. Scott; Bayesian Analysis, 2011, 6(1), pp. 1-23.

"Particle Learning of Gaussian Process Models for Sequential Design and Optimization." Robert B. Gramacy and Nicholas G. Polson; Journal of Computational and Graphical Statistics, 2011, 20(1), pp. 102-18.

"Dynamic Trees for Learning and Design." Matthew A. Taddy, Robert B. Gramacy and Nicholas G. Polson; Journal of the American Statistical Association, 2011, 106(493), pp. 109-23.

"Particle Learning for General Mixtures." Carlos M. Carvalho, Hedibert Freitas Lopes, Nicholas G. Polson and Matt A. Taddy; Bayesian Analysis, 2010, 5, pp. 709-40.

"Extracting S&P500 and Nasdaq Volatility: The Credit Crisis of 2007-2008," Hedibert F. Lopes and Nicholas G. Polson, in The Oxford Handbook of Applied Bayesian Analysis. A. O'Hagan and M. West, Oxford: Oxford University Press, 2010, pp. 319 - 42.

"The Horseshoe Estimator for Sparse Signals." Carlos M. Carvalho, Nicholas G. Polson and James G. Scott; Biometrika, 2010, 97(2), pp. 465-80.

"Optimal Filtering of Jump Diffusions: Extracting Latent States from Asset Prices." Michael S. Johannes, Nicholas G. Polson and Jonathan R. Stroud; Review of Financial Studies, 2009, 22(7), pp. 2759-99.

"Practical Filtering with Sequential Parameter Learning." Nicholas G. Polson, Jonathan R. Stroud and Peter Müller; Journal of the Royal Statistical Society. Series B: Statistical Methodology, 2008, 70(2), pp. 413-28.

"Mcmc Maximum Likelihood for Latent State Models." Eric Jacquier, Michael Johannes and Nicholas Polson; Journal of Econometrics, 2007, 137(2), pp. 615-40.

"Bayesian Analysis of Stochastic Volatility Models with Fat-Tails and Correlated Errors." Eric Jacquier, Nicholas G. Polson and Peter E. Rossi; Journal of Econometrics, 2004, 122(1), pp. 185-212.

"Nonlinear State-Space Models with State-Dependent Variances." Jonathan R. Stroud, Peter Muller and Nicholas G. Polson; Journal of the American Statistical Association, 2003, 98(462), pp. 377-86.

"Comment on 'Iterative and Recursive Estimation in Structural Nonadaptive Models'." Michael Johannes and Nicholas Polson; Journal of Business and Economic Statistics, 2003, 21(4), pp. 493-95.

"The Impact of Jumps in Volatility and Returns." Bjorn Eraker, Michael Johannes and Nicholas Polson; Journal of Finance, 2003, 58(3), pp. 1269-300.

"Bayesian Analysis of Stochastic Volatility Models." Eric Jacquier, Nicholas G. Polson and Peter E. Rossi; Journal of Business and Economic Statistics, 2002, 20(1), pp. 69-87.

"Where Will Yahoo! Stock Be in Five Years?" Nicholas G. Polson and Jeffrey Yasumoto; Chance, New Directions for Statistics and Computers, 2000, 13(3), pp. 25-28.

"Bayesian Portfolio Selection: An Empirical Analysis of the S&P 500 Index 1970-1996." Nicholas G. Polson and Bernard V. Tew; Journal of Business and Economic Statistics, 2000, 18(2), pp. 164-73.

"A Bayesian Analysis of the Multinomial Probit Model with Fully Identified Parameters." Robert E. McCulloch, Nicholas G. Polson and Peter E. Rossi; Journal of Econometrics, 2000, 99(1), pp. 173-93.

Stochastic Volatility : Univariate and Multivariate Extensions Éric Jacquier, Peter E. Rossi and Nicholas G. Polson; Série Scientifique = Scientific Series,; 99s-26; Variation: Série Scientifique (Cirano).; English ;; No. 99s-26.; Montréal: CIRANO, 1999.

"Convergence of Markov Chain Monte Carlo Algorithms," Nicholas G. Polson, in Bayesian Statistics 5 -- Proceedings of the Fifth Valencia International Meeting. J. M. Bernardo, J. O. Berger, A. P. Dawid and A. F. M. Smith, Oxford: Clarendon Press Oxford University Press, 1996, pp. 297-321.

"Diagnostic Measures for Model Criticism." Cinzia Carota, Giovanni Parmigiani and Nicholas G. Polson; Journal of the American Statistical Association, 1996, 91(434), pp. 753-62.

Stochastic Volatility : Univariate and Multivariate Extensions Eric Jacquier, Nicholas G. Polson and Peter Rossi; Rodney L. White Center for Financial Research ;; 19-95; Philadelphia, PA: Rodney L. White Center for Financial Research, 1995.

Bayesian Inference Nicholas Polson and George C. Tiao; Aldershot, U.K.: Elgar., 1995.

Models and Priors for Multivariate Stochastic Volatility Éric Jacquier, Peter E. Rossi and Nicholas G. Polson; Série Scientifique = Scientific Series,; No. 95s-18; Montréal: CIRANO, 1995.

"Sampling from Log-Concave Distributions (Corr: 94v4 P1255)." Alan Frieze, Ravi Kannan and Nick Polson; Annals of Applied Probability, 1994, 4(4), pp. 812-37.

"On the Geometric Convergence of the Gibbs Sampler." Gareth O. Roberts and Nicholas G. Polson; Journal of the Royal Statistical Society. Series B (Methodological), 1994, 56(2), pp. 377-84.

"Bayes Factors for Discrete Observations from Diffusion Processes." Nicholas G. Polson and Gareth O. Roberts; Biometrika, 1994, 81(1), pp. 11-26.

"Reply to Comments on 'Bayesian Analysis of Stochastic Volatility Models''." Eric Jacquier, Nicholas G. Polson and Peter E. Rossi; Journal of Business and Economic Statistics, 1994, 12(4), pp. 413-17.

"Bayesian Analysis of Stochastic Volatility Models." Eric Jacquier, Nicholas G. Polson and Peter E. Rossi; Journal of Business and Economic Statistics, 1994, 12(4), pp. 371-89.

Changes in Utility as Diagnostics Cinzia Carota, Giovanni Parmigiani and Nicholas G. Polson; Dp #93-A20.; Durham, N.C.: Institute of Statistics and Decision Sciences Duke University, 1993.

Sampling from Log-Concave Distributions Alan Frieze, Ravi Kannan and Nicholas G. Polson; Research Report 93-155.; Carnegie Mellon University Dept. of Mathematics, 1993.

"A Bayesian Perspective on the Design of Accelerated Life Tests," Nicholas G. Polson, in Advances in Reliability. A. P. Basu, New York; Amsterdam: Elsevier/North-Holland, 1993, pp. 321-30.

"Bayesian Model Criticism," Cinzia Carota, Giovanni Parmagiani and Nicholas G. Polson, in Asa Proceedings of the Section on Bayesian Statistical Science. Alexandria, VA: American Statistical Association, 1993, pp. 22-27.

"A Utility Based Approach to Information for Stochastic Differential Equations." Nicholas G. Polson and Gareth O. Roberts; Stochastic Processes and their Applications, 1993, 48(2), pp. 341-56.

"A Note on the Residual Entropy Function." Pietro Muliere, Giovanni Parmigiani and Nicholas G. Polson; Probability in the Engineering and Informational Sciences, 1993, 7, pp. 413-20.

A Note on the Residual Entropy Function Pietro Muliere, Giovanni Parmigiani and Nicholas G. Polson; Dp #92-A23; Durham, N.C.: Institute of Statistics and Decision Sciences Duke University, 1992.

"Bayesian Design for Random Walk Barriers," G. Parmigiani and N. G. Polson, in Bayesian Statistics 4. Proceedings of the Fourth Valencia International Meeting. J. M. Bernardo, J. O. Berger, A. P. Dawid and A. F. M. Smith, Oxford: Clarendon Press Oxford University Press, 1992, pp. 715-21.

"On the Expected Amount of Information from a Non-Linear Model." Nicholas G. Polson; Journal of the Royal Statistical Society. Series B (Methodological), 1992, 54(3), pp. 889-95.

"A Monte Carlo Approach to Nonnormal and Nonlinear State-Space Modeling." Bradley P. Carlin, Nicholas G. Polson and David S. Stoffer; Journal of the American Statistical Association, 1992, 87(418), pp. 493-500.

"Practical Markov Chain Monte Carlo : Comment." Nicholas G. Polson; Statistical Science, 1992, 7(4), pp. 490-91.

"Inference for Nonconjugate Bayesian Models Using the Gibbs Sampler." Bradley P. Carlin and Nicholas G. Polson; Canadian Journal of Statistics, 1991, 19, pp. 399-405.

"A Bayesian Decision Theoretic Characterization of Poisson Processes." Nicholas G. Polson and Gareth O. Roberts; Journal of the Royal Statistical Society. Series B (Methodological), 1991, 53(3), pp. 675-82.

"A Representation of the Posterior Mean for a Location Model." Nicholas G. Polson; Biometrika, 1991, 78(2), pp. 426-30.

"An Expected Utility Approach to Influence Diagnostics." Bradley P. Carlin and Nicholas G. Polson; Journal of the American Statistical Association, 1991, 86(416), pp. 1013-21.

"Review of 'Bayesian Statistics'." Nicholas G. Polson; Journal of the American Statistical Association, 1990, 85( 412), pp. 1167.

"Prior Distributions for the Bivariate Binomial." Nick Polson and Larry Wasserman; Biometrika, 1990, 77(4), pp. 901-04.

Bayesian Perspectives on Statistical Modelling; Nicholas G. Polson; Ph.D. Dissertation, University of Nottingham 1988.