Research

Interests

• Bayesian Nonparametric Methods
• Reliability and Survival Analysis
• Stochastic Processes
• Statistical and Probabilistic Computing

Published or Accepted Refereed Articles

• R. L. Warr, J. M. Meyer, and J. T. Curtis, A Bayesian Nonparametric System Reliability Model which Integrates Multiple Sources of Lifetime Information, Quality Engineering, available online.
• K. A. Batterton, C. M. Schubert, and R. L. Warr, A Fiducial-Based Confidence Interval for the Linear Combination of Multinomial Probabilities, Biometrical Journal, available online.
• R. L. Warr, J. E. Ritchie, and M. S. Hamada, Augmenting System Tests with Component Tests for Reliability Assurance, Journal of Quality Technology, 56, No. 2, 128-139 (2024).
• B. Hartman, C. Larsen, C. Kunkel, C. Wight, and R. L. Warr, A Two-Part Model of the Individual Costs of Chronic Kidney Disease, North American Actuarial Journal, 28, No. 1, 139-186 (2024).
• J. M. Clark and R. L. Warr, Bootstrapping through Discrete Convolutional Methods, Applied Stochastic Models in Business and Industry, 40, No. 1, 144-160 (2024).
• M. J. Heaton, B. K. Dahl, C. Dayley, R. L. Warr, and P. White, Integrating Machine Learning and Bayesian Nonparametrics for Flexible Modeling of Point Pattern Data, Computational Statistics and Data Analysis, 191, article 107875 (2024).
• G. G. Schultz, C. C. Lunt, T. Pew, and R. L. Warr, Using Complementary Intersection and Segment Analyses to Identify Crash Hot Spots, Safety Science, 163, article 106121 (2023).
• R. L. Warr, D. B. Dahl, J. M. Meyer, and A. Lui, The Attraction Indian Buffet Distribution, Bayesian Analysis, 17, No. 3, 931-967 (2022). Associated software package on CRAN: aibd.
• G. G. Schultz, C. C. Lunt, T. Pew, and R. L. Warr, Using Complementary Intersection and Segment Analyses to Identify Crash Hot Spots (Extended Summary), 8th Road Safety and Simulation Conference Proceedings, (2022).
• D. B. Dahl, R. L. Warr, and T. P. Jensen, Invited Discussion of: “Centered Partition Processes: Informative Priors for Clustering," Bayesian Analysis, 16, No. 1, 333–338 (2021).
• T. Pew, R. L. Warr, G. G. Schultz, and M. Heaton, Justification for Considering Zero-Inflated Models in Crash Frequency Analysis, Transportation Research Interdisciplinary Perspectives, 8, article 100249 (2020).
• R. L. Warr and C. J. Wight, Error Bounds for Cumulative Distribution Functions of Convolutions via the Discrete Fourier Transform, Methodology and Computing in Applied Probability, 22, No. 3, 881-904 (2020).
• R. L. Warr and T. B. Woodfield, Bayesian Nonparametric Estimation of First Passage Distributions in Semi-Markov Processes, Applied Stochastic Models in Business and Industry, 36, No. 2, 237-250 (2020).
• R. L. Warr and J. D. Cordeiro, First Passage Moments of Finite-State Semi-Markov Processes, Journal of the Indian Statistical Association, 57, No. 2, 145-172 (2019).
• J. K. Freels, D. A. Timme, J. J. Pignatiello, R. L. Warr, and R. R. Hill, Maximum Likelihood Estimation for the Poly-Weibull Distribution, Quality Engineering, 31, No. 4, 545–552 (2019).
• D. H. Collins and R. L. Warr, Failure Time Distributions for Complex Equipment, Quality and Reliability Engineering International, 35, No. 1, 146–154 (2019).
• B. P. Weaver, R. L. Warr, C. M. Anderson-Cook, and D. M. Higdon, Visualizing Discrepancies from Nonlinear Models and Computer Experiments, Statistical Analysis and Data Mining, 8, No. 5-6, 274–286 (2015).
• J. K. Freels, J. J. Pignatiello, R. L. Warr and R. R. Hill, Bridging the Gap between Quantitative and Qualitative Accelerated Life Tests, Quality and Reliability Engineering International, 31, No. 5, 789–800 (2015).
• R. L. Warr and D. H. Collins, A Comprehensive Method for Solving Finite-State Semi-Markov Processes, International Journal of Simulation and Process Modelling, 10, No. 1, 89–99 (2015). Pre-publication manuscript
• R. L. Warr, Numerical Approximation of Probability Mass Functions via the Inverse Discrete Fourier Transform, Methodology and Computing in Applied Probability, 16, No. 4, 1025–1038 (2014).
• M. S. Hamada and R. L. Warr, Analyzing Deficient Response Summaries From Designed Experiments, Quality Engineering, 26, No. 4, 440–449 (2014).
• R. L. Warr and D. H. Collins, Bayesian Nonparametric Models for Combining Heterogeneous Reliability Data, Journal of Risk and Reliability, 228, No. 2, 166–175 (2014).
• R. L. Warr and R. A. Erich, Should the Interquartile Range Divided by the Standard Deviation be used to Assess Normality?, The American Statistician, 67, No. 4, 242–244 (2013).
• D. H. Collins, R. L. Warr, and A. V. Huzurbazar, An Introduction to Statistical Flowgraph Models for Engineering Systems, Journal of Risk and Reliability, 227, No. 5, 461–470 (2013).
• D. H. Collins, J. K. Freels, A. V. Huzurbazar, R. L. Warr, and B. P. Weaver, Accelerated Test Methods for Reliability Prediction, Journal of Quality Technology, 45, No. 3, 244–259 (2013). Won the 2014 Lloyd S. Nelson Award.
• R. L. Warr and A. V. Huzurbazar, Expanding the Statistical Flowgraph Model Framework to use any Transition Distribution, Journal of Statistical Theory and Practice, 4, No. 4, 529–539 (2010).

Other Works

• M. S. Hamada, T. L. Graves, N. W. Hengartner, D. M. Higdon, A. V. Huzurbazar, E. C. Lawrence, C. D. Linkletter, C. S. Reese, D. W. Scott, R. R. Sitter, R. L. Warr, and B. J. Williams, Quality Quantries: Using Simulation to Handle Implicit Likelihoods in a Bayesian Analysis, Quality Engineering, 33, No. 1, 172–177 (2021).
• Quality Quandaries: Estimating Correlations with Censored Data Quality Quandaries: Estimating Correlations, Quality Engineering, 32, No. 3, 521–527 (2020).
• A. V. Huzurbazar and R. L. Warr, Statistical Flowgraph Models, Wiley StatsRef: Statistics Reference Online, 1–10 (2018).

Letters to the Editor

• R. L. Warr and R. A. Erich, Response to the Letter to the Editor: Should the Interquartile Range Divided by the Standard Deviation be used to Assess Normality?, The American Statistician, 68, No. 4, 317 (2014).

Proceedings

• R. L. Warr and D. H. Collins. 2012. Bayesian Nonparametric Models for Combining Heterogeneous Reliability Data. In JSM Proceedings, Physical and Engineering Sciences Section. Alexandria, VA: American Statistical Association. 2220-2232.

Technical Reports

• M. S. Hamada, T. L. Graves, N. W. Hengartner, D. M. Higdon, A. V. Huzurbazar, E. C. Lawrence, C. D. Linkletter, C. S. Reese, D. W. Scott, R. R. Sitter, R. L. Warr, B. J. Williams, A Note on Using Discretized Simulated Data to Estimate Implicit Likelihoods in Bayesian Analyses, arXiv preprint arXiv:2008.02926 (2020).
• D. H. Collins, J. K. Freels, A. V. Huzurbazar, R. L. Warr, and B. P. Weaver, Accelerated Test Methods for Reliability Prediction, 134–135, LA-UR-12-20429 (2012).
• R. R. Picard, B. J. Williams, L. P. Swiler, A. Urbina and R. L. Warr, Multiple Model Inference with Applications to Uncertainty Quantification for Complex Codes. Los Alamos National Lab Technical Report LA-UR-10-06382 (2010).
• E. D. White and R. L. Warr, Teaching Bayes' Rule using Mosaic Plots, arXiv preprint arXiv:2112.00162 (2021).