Working Papers

• Clustering County-Level Mortality Curves in the United States
  C. Syndergaard, B. Hartman, R. Richardson, C. Groendyke
  Submitted
• A Multivariate Spatiotemporal Model for County Level Mortality Data in the Contiguous United States
  M. Shull, R. Richardson, C. Groendyke, B. Hartman
  Submitted
• Equitable Handicap System with Application in Disc Golf
  M. Gerratt, D. Buursma, B. Hartman
  Submitted

Refereed Publications

• Using Dynamic Linear Models with Changepoints to Understand Trends in the Auto Insurance Industry
  R. Richardson, B. Hartman, S. Allen, J. Anderson, M. Christensen, M. Gerratt, and A. Walker
  To appear in Variance
  Appendix
• Synthesizing Property & Casualty Ratemaking Datasets using Generative Adversarial Networks
  M.-P. Cote, B. Hartman, O. Mercier, J. Meyers, J. Cummings, and E. Harmon
  To appear in Variance
• A Two-Part Model of the Individual Costs of Chronic Kidney Disease
  B. Hartman, C. Larson, C. Kunkel, C. Wight, R. Warr
  North American Actuarial Journal. 28(1), 139-186, 2023.
  Podcast
  Preprint
• Predicting Ambulatory Care Sensitive Emergency Department Admissions
  A. Ott, B. Zabriskie, and B. Hartman
  Journal of Health Policy and Hospital Management. 6, 2022.
• Using Machine Learning to Better Model Long-term Care Insurance Claims
  J. Cummings and B. Hartman
  North American Actuarial Journal. 26(3), 470-483, 2022.
  Preprint
• Market-based Model Selection for Commercial Auto Ratemaking
  B. Hartman, C. Dixon, and A. Walch
  Variance. 15(1), 2022.
  Preprint
• Machine Learning in Ratemaking, an Application in Commercial Auto Insurance
  S. Matthews, B. Hartman
  Risks, 10(4), 80, 2022.
  Preprint
• mSHAP: SHAP Values for Two-part Models
  S. Matthews and B. Hartman
  Risks, 10(3). 2022.
  R package (on CRAN)
  Preprint
• A Bayesian Approach to Real-time Spatiotemporal Prediction Systems for Respiratory Syncytial Virus
  M. Heaton, C. Ingersoll, C. Berrett, B. Hartman, and C. Sloan
  Spatial and Spatio-temporal Epidemiology. 38. August 2021.
  Preprint
• Using Asymmetric Cost Matrices to Optimize Wellness Intervention
  Z. Gibbs and B. Hartman
  North American Actuarial Journal. 25:1, 62-72. 2021.
  Preprint
• Predicting High-cost Health Insurance Members through Boosted Trees and Oversampling: An Application Using the HCCI Database
  B. Hartman, R. Owen, and Z. Gibbs
  North American Actuarial Journal. 25:1, 53-61. 2021.
  Preprint
• Modeling County-level Spatio-temporal Mortality Rates using Dynamic Linear Models
  Z. Gibbs, C. Groendyke, B. Hartman, and R. Richardson
  Risks. 8(4), 117. 2020.
  Preprint
• Bayesian Multivariate Regime-switching Models and the Impact of Correlation Structure Misspecification in Variable Annuity Pricing
  B. Hartman, C. Groendyke, and D. Engler
  Scandinavian Actuarial Journal. 2020:2. 152-171. 2020.
  Preprint
• Estimating Seasonal Onsets and Peaks of Bronchiolitis with Spatially and Temporally Uncertain Data
  S. Pugh, M. Heaton, B. Hartman, C. Berrett, C. Sloan, A. Evans, G. Tebeb, P. Wu, T. Hartert, and R. Lee
  Statistics in Medicine, 38(11), 1991-2001, 2019.
• Bayesian Nonparametric Regression Models for Modeling and Predicting Healthcare Claims
  R. Richardson and B. Hartman
  Insurance: Mathematics and Economics, 83, 1-8, 2018.
  Preprint
• Estimating Loss Reserves Using Hierarchical Bayesian Gaussian Process Regression with Input Warping
  Code:    GPIso    GPAnIso    GPAdditive
  N. Lally and B. Hartman
  Insurance: Mathematics and Economics, 82, 124-140, 2018.
  Preprint
• Estimated Time of Restoration (ETR) Guidance for Electric Distribution Networks
  D. W. Wanik, J. He, T. Layton, E. N. Anagnostou, B. M. Hartman
  Journal of Homeland Security and Emergency Management, 15(1), 1-13, 2018.
  Preprint
• A Case Study on Power Outage Impacts from Future Hurricane Sandy Scenarios
  D. W. Wanik, E. N. Anagnostou, M. Astitha, B. M. Hartman, M. E. B. Frediani, G. M. Lackmann, J. He, and J. Yang
  Journal of Applied Meteorology and Climatology, 57(1), 51-79, 2018.
  Preprint
• Nonparametric Tree-based Predictive Modeling of Storm Damage to Power Distribution Network
  J. He, D. W. Wanik, B. M. Hartman, E. N. Anagnostou, M. Astitha, and M. E. B. Frediani
  Risk Analysis, 37(3), 441-458, 2017.
  Preprint
• Using a Bayesian regression approach on dual-model weather simulations to improve wind speed prediction
  J. Yang, M. Astitha, E. N. Anagnostou, B. M. Hartman
  Journal of Applied Meteorology and Climatology, 56(4), 1155-1174, 2017.
  Preprint - Supplement
• Using Vegetation Management and LiDAR-Derived Tree Height Data to Improve Outage Predictions for Electric Utilities
  D. W. Wanik, J. R. Parent, E. N. Anagnostou, and B. M. Hartman
  Electric Power Systems Research, 146, 236-245, 2017.
  Preprint
• Model Selection and Averaging of Health Costs in Episode Treatment Groups
  S. Huang, B. M. Hartman, and V. Brazauskas
  ASTIN Bulletin, 47(1), 153-167, 2017.
  Preprint
• Predictive Modeling in Long Term Care Insurance
  N. R. Lally and B. M. Hartman
  North American Actuarial Journal, 20(2), 160-183, 2016.
  Preprint
• Credibility in Loss Reserving
  P. Shi and B. M. Hartman
  North American Actuarial Journal, 20(2), 114-132, 2016.
  Preprint
• Storm Outage Modeling for an Electric Distribution Network in Northeastern USA
  D. W. Wanik, E. N. Anagnostou, B. M. Hartman, M. E. B. Frediani, and M. Astitha
  Natural Hazards, 79(2), 1359-1384, 2015.
  Preprint
• Bayesian Nonparametric Predictive Modeling of Group Health Claims
  G. W. Fellingham, A. Kottas, and B. M. Hartman
  Insurance: Mathematics and Economics, 60, 1-10, 2015.
  Preprint
• Model Selection and Averaging in Financial Risk Management
  B. M. Hartman and C. Groendyke
  North American Actuarial Journal, 17(3), 216-228, 2013.
  Preprint
• Investigating International New Product Diffusion Speed: A Semiparametric Approach
  B. M. Hartman, B. K. Mallick, and D. Talukdar
  Annals of Applied Statistics, 6(2), 625-651, 2012.
  Preprint
• Accounting for regime and parameter uncertainty in regime-switching models
  B. M. Hartman and M. J. Heaton
  Insurance: Mathematics and Economics, 49(3), 429-437, 2011.
  Preprint

Other Publications

• Principle-Based Reserves Simplified Methods
  M. Birdsall, S. Strommen, and B. Hartman
  Society of Actuaries Report, 2020
• Auto Loss Costs Trend Analysis
  B. Hartman, B. Allen, E. Bingham, S. Fenwick, E. Hanks, S. J. Hansen, E. Harmon, B. Heywood, T. Johnson, and C. Wight.
  Casualty Actuarial Society, PCI, and Society of Actuaries Report, 2018
• Parameter Uncertainty
  B. Hartman, R. Richardson, and R. Bateman
  CAS, CIA, and SOA Report, Apr. 2017
• Learning to Untangle: Training Actuaries to Solve Problems with Data
  B. M. Hartman
  The Actuary, Jun/Jul 2016
• James C. Hickman Scholar Program: Building Future Actuarial Educators
  B. M. Hartman and C. Groendyke
  The Actuary, Jun/Jul 2015
• Bayesian Computation
  B. M. Hartman
  In J. Frees, G. Meyers, and R. Derrig (Eds.), Predictive Modeling Applications in Actuarial Science. Cambridge University Press, 2014.
• Asset Returns from a Distance-Based Random Partition Model.
  R. D. Payne, B. M. Hartman, and D. B. Dahl
  Technical Report, 2013
  Summary
• Investigating Cross-Country Influence Dynamics in New Product Diffusion
  B. M. Hartman, B. K. Mallick, K Sudhir, and D. Talukdar
  Technical Report, 2011
• Bayesian Nonparametric Regression for Diabetes Deaths
  B. M. Hartman and D. B. Dahl
  Actuarial Research Clearing House 2010.1
• Assessing Model Uncertainty Using Reversible Jump MCMC
  B. M. Hartman and J. D. Hart
  Actuarial Research Clearing House. 2009.1