Research Contributions of Jeffrey S. Rosenthal

Hello! Bonjour! ¡Buenos días! Buon giorno! Guten Tag! Bom dia! Welcome to my research page. My research interests include probability theory, Markov chains, stochastic processes, and statistical computation especially Markov chain Monte Carlo computer algorithms. My research papers are provided below, grouped by year of initial submission, with multiple authors often listed alphabetically. Many of the papers are provided in postscript format; to view them use e.g. ghostview. Most of them are also provided in pdf format; to view them use e.g. Adobe Reader or xpdf or ghostview. Many are joint with Gareth Roberts (see photo1, photo2, photo3, photo4, photo5). Some of my research involves interdisciplinary applications to subjects outside of my usual fields of statistics/mathematics/computation, mentioned below in {curly brackets}. See also my Markov chain Java applets and Javascript, an on-line research talk, and my non-research writings, and my biography.

Shortcuts to selected ... review papers: galinart / probsurv / computsimple / scalerev / bruns / gentheory / eigen

... research papers: adversarial / amcmc / adaptex / adapt / determ / one-shot / period / hobertfinal / suffic / slice / hybrid / sens / lang / james / minor / varnew / rots

... books: Rigorous Probability / Struck by Lightning / Science of Uncertainty / Knock on Wood / Stochastic Processes

... years: 2024 / 2023 / 2022 / 2021 / 2020 / 2019 / 2018 / 2017 / 2016 / 2015 / 2014 / 2013 / 2012 / 2011 / 2010 / 2009 / 2008 / 2007 / 2006 / 2005 / 2004 / 2003 / 2002 / 2001 / 2000 / 1999 / 1998 / 1997 / 1996 / 1995 / 1994 / 1993 / 1992 / 1989 / Books / Other / Misc

I frequently give research lectures; see e.g. my 2017 lectures at UBC/2/poster and Purdue/video and Warwick/poster and Warwick2 and Oxford, and this 2020 McGill talk and the slides for this DSSS talk and a 2023 Waterloo talk.

2024:

M. Cullip, J.S. Rosenthal, R. Wells, and J.M. Dmetrichuk, Where are we now? Retrospective study of non-natural deaths in Ontario. [pdf]
A. Brown and J.S. Rosenthal, Weak convergence of adaptive Markov chain Monte Carlo. [pdf]
A. Li, L. Wang, T. Dou, and J.S. Rosenthal, Exploring the generalizability of the optimal 0.234 acceptance rate in random-walk Metropolis and parallel tempering algorithms. [pdf]
G.T. Salmon and J.S. Rosenthal, Comparing the Efficiency of General State Space Reversible MCMC Algorithms. [pdf, arXiv]

2023:

R.M. Neal and J.S. Rosenthal, Efficiency of Reversible MCMC Methods: Elementary Derivations and Applications to Composite Methods. [pdf, postscript, arXiv, related blog post] J. Appl. Prob., to appear.
D. Ledvinka and J.S. Rosenthal, Equivalence of Starting Point Cutoff and the Concentration of Hitting Times on a General State Space. [pdf, Appendix]
S. Sixta, J.S. Rosenthal, and A. Brown, Bounding and estimating MCMC convergence rates using common random number simulations. [pdf, arXiv]
J.S. Rosenthal, Optimising and Adapting Metropolis Algorithm Proposal Distributions [pdf]. (Chapter for Handbook of MCMC, 2nd ed., 2024. Update of previous version.)

2022:

J.J. Slater, P.E. Brown, J.S. Rosenthal, and J. Mateu, Leveraging cellphone-derived mobility networks to assess COVID-19 travel risk. [pdf] Ann. Appl. Stat., to appear. {Health}
S. Chen, J.S. Rosenthal, A. Dote, H. Tamura, and A. Sheikholeslami, Sampling via Rejection-Free Partial Neighbor Search. [pdf, arXiv, pub, online] Comp. Stat. & Data Anal., to appear. {Technology}
J.S. Rosenthal, How Markov's Little Idea Transformed Statistics. [pdf, published, online] Book chapter in Handbook Hist. Phil. Math. Practice, B. Sriraman, ed., 2023. Pages 1371-1381.
M.A. Gallegos-Herrada, D. Ledvinka, and J.S. Rosenthal, Equivalences of Geometric Ergodicity of Markov Chains [pdf, ps, arXiv, published, online, praise] J. Theoretical Prob. 37:1230-1256, 2024.
J.J. Slater, A. Bansal, H. Campbell, J.S. Rosenthal, P. Gustafson, and P.E. Brown, A Bayesian Approach to Estimating COVID-19 Incidence and Infection Fatality Rates. [pdf, pub] Biostatistics 25(2):354-384, Apr 2024. {Health}
S. Chen, J.S. Rosenthal, A. Dote, H. Tamura, and A. Sheikholeslami, Optimization via Rejection-Free Partial Neighbor Search. [pdf, arXiv, published] Stat. and Comput. 33(6), article 131, Dec 2023. {Technology}
G.O. Roberts and J.S. Rosenthal, Football Group Draw Probabilities and Corrections. [pdf, arXiv, published, online] Can. J. Stat. 52(3):659-677, 2024. (See also the simulations / Toronto Star / UofT News / CBC article / UEFA.) {Sports}

2021:

G.O. Roberts and J.S. Rosenthal, Polynomial Convergence Rates of Piecewise Deterministic Markov Processes. [pdf, published, online] MCAP 25(6):5-18, 2023.
J.J. Slater, P.E. Brown, J.S. Rosenthal, and J. Mateu, Capturing Spatial Dependence of COVID-19 Case Counts with Cellphone Mobility Data. [pdf, published, online] Spatial Statistics 100540, 2022. {Health}
G.M. Eadie, J.J. Webb, and J.S. Rosenthal, Bayesian Inference of Globular Cluster Properties using Distribution Functions. [pdf, arXiv, published, online] Astrophysical J. 926(2):211, 2022. {Astronomy}
A. Dharamshi, V. Ngo, and J.S. Rosenthal, Sampling by Divergence Minimization. [pdf, arXiv, pub, online, eprint] Comm Stat - Sim & Comp, to appear.
Q. Zhou, Jun Yang, D. Vats, G.O. Roberts, and J.S. Rosenthal, Dimension-free Mixing for High-dimensional Bayesian Variable Selection. [pdf, arXiv, published, online] JRSSB 84(5):1751-1784, 2022.
J.M. Dmetrichuk, J.S. Rosenthal, J. Man, M. Cullip, and R.A. Wells, Non-Natural Manners of Death in Ontario: Effects of the COVID-19 Pandemic and Related Public Health Measures [pdf, published, Tech Supp, Ages Supp, online, publicity1, publicity2] Lancet Reg. Health Am. 7:100130, March 2022. {Health}
R.V. Craiu, P. Gustafson, and J.S. Rosenthal, Reflections on Bayesian Inference and Markov Chain Monte Carlo. [pdf, published, online] Can. J. Stat. 50(4):1213-1227, 2022.
S. Sixta and J.S. Rosenthal, Convergence Rate Bounds for Iterative Random Functions Using One-Shot Coupling. [pdf, arXiv, published] Stat. and Comput. 32(5), article 71, Oct 2022.
D. Rosenthal and J.S. Rosenthal, Optimal Strategies and Rules for the Game of Horse. [pdf, arXiv, published, online, photo, UofT News story] Notices of the AMS 69(6):1014-1017, June/July 2022. {Sports}

2020:

C. Beaulac, J.S. Rosenthal, Q. Pei, D. Friedman, S. Wolden, and D. Hodgson, An evaluation of machine learning techniques to predict the outcome of children treated for Hodgkin-Lymphoma. [pdf, published, pubmed, tweet] Applied Artificial Intelligence 34(14):2020, 1100-1114. {Health}
J.S. Rosenthal, Maximum Binomial Probabilities and Game Theory Voter Models. [pdf, ps, published] Adv. Appl. Stat. 64(1):2020, 75-85. {Game Theory}
J.S. Rosenthal and A.H. Yoon, The Salience and Longevity of Judicial Precedent: A Case Study of the U.S. Supreme Court. [pdf] (Unpublished manuscript.) {Law}
Y.H. Jiang, T. Liu, Z. Lou, J.S. Rosenthal, S. Shangguan, F. Wang, and Z. Wu, The Coupling/Minorization/Drift Approach to Markov Chain Convergence Rates. [pdf, appendix, combined, arXiv, published, tweet] Notices of the AMS, April 2021, 471-479.
J.J. Slater, P.E. Brown, and J.S. Rosenthal, Forecasting subnational COVID-19 mortality using a day-of-the-week adjusted Bayesian hierarchical model. [pdf / online] Stat (ISI) 10(1):e328, 2021. {Health}
G.O. Roberts, J.S. Rosenthal, and N.G. Tawn, Skew Brownian Motion and Complexity of the ALPS Algorithm. [pdf, arXiv, online] J. Appl. Prob. 59(3):777-796, 2022.
C. Beaulac and J.S. Rosenthal, Introducing a high-resolution hand-written digits data set with writer characteristics. [pdf, arXiv, published] SN Computer Science 4:66, 2023.
Y.H. Jiang, T. Liu, Z. Lou, J.S. Rosenthal, S. Shangguan, F. Wang, and Z. Wu, MCMC Confidence Intervals and Biases. [pdf, arXiv, published, online, tweet] Int. J. Stat. Prob. 11(1):29-39, January 2022.
Y.H. Jiang, T. Liu, Z. Lou, J.S. Rosenthal, S. Shangguan, F. Wang, and Z. Wu, Convergence Rates of Attractive-Repulsive MCMC Algorithms. [pdf, arXiv, published] MCAP 24:2029-2054, 2022.

2019:

Jun Yang, G.O. Roberts, and J.S. Rosenthal, Optimal Scaling of Random-Walk Metropolis Algorithms on General Target Distributions. [pdf, arXiv, journal, published] Stoch. Proc. Appl. 130:6094-6132, 2020.
Z. Guo, I. Khuu, K. Zhu, J.S. Rosenthal, and F.P. Schoenberg, Distinguishing Luck from Skill through Statistical Simulation: A Case Study. [pdf, B&W, online, eprint, pub, publicity] Comm. Stat. - Sim. and Comp. 51(5):2537-2559, 2022.
J.S. Rosenthal, A. Dote, K. Dabiri, H. Tamura, S. Chen, and A. Sheikholeslami, Jump Markov Chains and Rejection-Free Metropolis Algorithms. [pdf, arXiv, published, online] Computational Statistics 36:2789-2811, 2021. {Technology}

2018:

C. Beaulac and J.S. Rosenthal, BEST : A decision tree algorithm that handles missing values. [pdf, arXiv, published] Computational Statistics 35(3):1001-1026, 2020.
R. Entezari, P.E. Brown, and J.S. Rosenthal, Bayesian Spatial Analysis of Hardwood Tree Counts in Forests via MCMC. [pdf, supplement, arXiv] Environmetrics 31(4), June 2020. {Forestry}
N.G. Tawn, G.O. Roberts, and J.S. Rosenthal, Weight-Preserving Simulated Tempering. [pdf / arXiv / published / online] Stat. and Comput. 30:27-41, 2020. See also a related talk.
C. Beaulac, J.S. Rosenthal, and D. Hodgson, A Deep Latent-Variable Model Application to Select Treatment Intensity in Survival Analysis. [pdf.] NeurIPS 2018 ML4H workshop (digital acceptance).

2017:

H. Duanmu, J.S. Rosenthal, and W. Weiss, Ergodicity of Markov Processes via Nonstandard Analysis (153 pages). [pdf, ps, published] (See also research announcement / ps.) Memoirs of the AMS 273(1342):1-114, 2021.
P.A. Ernst, W.S. Kendall, G.O. Roberts, and J.S. Rosenthal, MEXIT: Maximal un-coupling times for Markov processes. [pdf, ps, arXiv, published] Stoch. Proc. Appl. 129(2):355-380, 2019.
J. Negrea and J.S. Rosenthal, Approximations of Geometrically Ergodic Reversible Markov Chains. [pdf, arXiv, online] J. Appl. Prob. 53(4):981-1022, 2021.
J.S. Rosenthal, Many-Candidate Nash Equilibria for Elections Involving Random Selection. [pdf, ps, journal, published]. (See also the related software.) MCAP 21(1):279-293, 2019. {Game Theory}
Jun Yang and J.S. Rosenthal, Complexity Results for MCMC derived from Quantitative Bounds. [pdf, arXiv, published]. Ann. Appl. Prob. 33(2):1459-1500, 2023.
C. Beaulac and J.S. Rosenthal, Predicting University Students' Academic Success and Choice of Major using Random Forests. Res. Higher Ed. 60(7):1048-1064, 2019. [pdf, arXiv, published]

2016:

Jinyoung Yang, E. Levi, R.V. Craiu, and J.S. Rosenthal, Adaptive Component-wise Multiple-Try Metropolis Sampling. [pdf, arXiv, published] J. Comp. Graph. Stat. 28(2):267-289, 2019.
R. Entezari, R.V. Craiu, and J.S. Rosenthal, Likelihood Inflating Sampling Algorithm. [pdf / appendix / arXiv / published]. Can. J. Stat. 46(1):147-175, 2018. (Received CJS best paper award.) (See also a related discussion in Bayesian Analysis 11(3):935-937, 2016.)
J.S. Rosenthal, Nash Equilibria for Voter Models with Randomly Perceived Positions [pdf, published]. (See also a slightly-related lemma, and the related Osborne conjecture.) (Stochastic Models 34(1):98-114, 2018.) {Game Theory}
J.S. Rosenthal, Stochastic Simulation of Sequential Game-Theory Voting Models [pdf, published, free-online, published-pdf]. (See also the related Java applet.) (Comm. Stat.: Sim. and Comp. 47(7):2040-2054, 2018.) {Game Theory}
M.J. Osborne, J.S. Rosenthal, and C. Stewart, Information aggregation with costly reporting [pdf, supplement, published]. (The Economic Journal 130(625):208-232, 2020.) {Game Theory}
J.S. Rosenthal, Simple Confidence Intervals for MCMC Without CLTs. [pdf, ps, abstract, arXiv, journal, published]. Elec J Stat 11:211-214, 2017.
G.O. Roberts and J.S. Rosenthal, Hitting Time and Convergence Rate Bounds for Symmetric Langevin Diffusions. [pdf, ps, arXiv, published]. MCAP 21(3):921-929, 2019.

2015:

G.O. Roberts and J.S. Rosenthal, Surprising Convergence Properties of Some Simple Gibbs Samplers Under Various Scans [pdf, journal, published]. Int. J. Stat. Prob. 5:51-60, 2016.
J.S. Rosenthal and Jinyoung Yang, Ergodicity of Combocontinuous Adaptive MCMC Algorithms. [pdf / published / blog post]. MCAP 20(2):535-551, 2018.
J.S. Rosenthal and P. Rosenthal, Spectral Bounds for Certain Two-Factor Non-Reversible MCMC Algorithms. [pdf, ps, published] Elec. Comm. Prob. 20:1-10, 2015.
M. Gollob, J.S. Rosenthal, and K.E. Thorpe, The Probability of Pathogenicity in Clinical Genetic Testing: A Solution for the Variant of Uncertain Significance. [pdf, ps, published, online] (See also our related online calculator.) Int. J. Stat. Prob. 5(4):52-58, 2016.

2014:

R.V. Craiu, L. Gray, K. Latuszynski, N. Madras, G.O. Roberts, and J.S. Rosenthal, Stability of Adversarial Markov Chains, with an Application to Adaptive MCMC Algorithms [pdf, postscript, arXiv, published]. Ann. Appl. Prob. 15(6):3592-3623, 2015. (See also somewhat-related talk #1 / #2.)
J.S. Rosenthal, Interdisciplinary Sojourns [pdf, postscript]. (Article upon winning the SSC Gold Medal; see also my SSC Gold Medal talk slides and some spoof song lyrics and audio file / mp3 and photo). Can. J. Stat. 42(4):509-524, 2014.
G.O. Roberts and J.S. Rosenthal, Complexity Bounds for MCMC via Diffusion Limits. [pdf, postscript, published] J. Appl. Prob. 53(2):410-420, 2016.
Jinyoung Yang and J.S. Rosenthal, Automatically Tuned General-Purpose MCMC via New Adaptive Diagnostics [in pdf only]. Computational Statistics 32(1):315-348, 2017. (See also the related R package `atmcmc' and manual.)

2013:

C. Sherlock, A.H. Thiery, G.O. Roberts, and J.S. Rosenthal, On the efficiency of pseudo-marginal random walk Metropolis algorithms [pdf / arXiv / galleys / published]. Ann. Stat. 43:238-275, 2015.
K. Latuszynski and J.S. Rosenthal, The Containment Condition and AdapFail Algorithms [pdf, postscript, arXiv]. J. Appl. Prob. 51(4):1189-1195, 2014. (See also this wonderful tribute card/poster.)
J.S. Rosenthal, Optimising and Adapting the Metropolis Algorithm [pdf, published]. (Short review chapter for the SSC volume Statistics in Action: A Canadian Outlook, 2014. See also the related Java applet.)
R.V. Craiu and J.S. Rosenthal, Bayesian Computation via Markov chain Monte Carlo [pdf, postscript, published]. (Review paper for Annual Review of Statistics and Its Application 1:179-201, 2014.)
Y. Yunusova, J.S. Rosenthal, J.R. Green, S. Shellikeri, J. Wang, and L. Zinman, Detection of Bulbar ALS using a comprehensive speech assessment battery [pdf]. (MAVEBA 2013 conference proceedings.)

2012:

G.L. Jones, G.O. Roberts, and J.S. Rosenthal, Convergence of Conditional Metropolis-Hastings Samplers [pdf, postscript]. (J. Appl. Prob. 46:422-445, 2014.
K. Bodwin, J.S. Rosenthal, and A.H. Yoon, Opinion Writing and Authorship on the Supreme Court of Canada [pdf]. U. Toronto Law J. 63:159-192, 2013. (See the related software.) {Law}
P.E. Brown, F. Chimard, A. Remorov, J.S. Rosenthal, and X. Wang, Statistical Inference and Computational Efficiency for Spatial Infectious-Disease Models with Plantation Data [pdf, pub]. (JRSSC (Applied Statistics) 63:467-482, 2014.
G.O. Roberts and J.S. Rosenthal, Minimising MCMC Variance via Diffusion Limits, with an Application to Simulated Tempering [pdf, postscript, published]. Ann. Appl. Prob. 24:131-149, 2014.
K. Bodwin, J.S. Rosenthal, and A.H. Yoon, A Statistical Approach to Judicial Authorship: A Case Study of Judge Easterbrook [pdf, reprint]. Adv. Appl. Stat.:37(2) (2013), 123-148. {Law}
D.M. Day, J.D. Nielsen, A.K. Ward, J.S. Rosenthal, Y. Sun, I. Bevc, and T. Duchesne, Criminal Trajectories of Two Subsamples of Adjudicated Ontario Youths. Report for Canada's National Crime Prevention Centre. [pdf, French pdf, NCPC site, NCPC French site]. {Criminology}
M.A. Bailey, J.S. Rosenthal, and A.H. Yoon, Grades and Incentives: Assessing Competing GPA Measures and Post-Graduate Outcomes [pdf, published]. Stud. Higher Ed. 41:1548-1562, 2015. (See also the related software.) {Education}
G.O. Roberts and J.S. Rosenthal, A Note on Formal Constructions of Sequential Conditional Couplings. [pdf, postscript] (Stat. Prob. Lett. 83:2073-2076, 2013.)

2011:

Y. Yunusova, J.S. Rosenthal, K. Rudy, M. Baljko, and J. Daskalogiannakis, Place of articulation for lingual consonants defined using electromagnetic articulography [pdf]. J. Acoustical Soc. Am. 132:1027-1038, 2012. {Health}
D.B. Woodard and J.S. Rosenthal, Convergence rate of Markov chain methods for genomic motif discovery [pdf paper, pdf Appendix, ps paper, published version]. Ann. Stat. 41:91-124, 2013.
J.D. Nielsen, J.S. Rosenthal, Y. Sun, D.M. Day, I. Bevc, and T. Duchesne, Group-based Criminal Trajectory Analysis using Cross-Validation Criteria. [pdf, postscript] (See also the related software.) Comm. in Stat. - Theory & Meth. 43:4337-4356, 2014. {Criminology}
K. Latuszynski, G.O. Roberts, and J.S. Rosenthal (see photo), Adaptive Gibbs samplers and related MCMC methods. [pdf, postscript, arXiv] Ann. Appl. Prob. 23(1):66-98, 2013.
J.S. Rosenthal, Was the Conservative majority predictable? [pdf, postscript] Can. J. Stat. 39:721-733, 2011. See also the related software and a mayoral endorsement. {Political Science}
D.M. Day, J.D. Nielsen, A.K. Ward, Y. Sun, J.S. Rosenthal, I. Bevc, T. Duchesne, and L. Rossman, Trajectories of Criminal Activity in a Sample of 378 Adjudicated Ontario Youth. [pdf paper, pdf poster] Presented at the 72nd annual CPA conference / 2nd NACCJPC conference, Toronto, June 2, 2011. {Criminology}

2010:

J.S. Rosenthal and A.H. Yoon, Judicial Ghostwriting: Authorship on the U.S. Supreme Court [in pdf only]. Cornell Law Review 96:1307-1343, 2011. (See also the New York Times summary, related talk / French, and the related software.) {Law}
A.K. Ward, D.M. Day, I. Bevc, Y. Sun, J.S. Rosenthal, and T. Duchesne, Criminal Trajectories and Risk Factors in a Canadian Sample of Offenders [in pdf only]. (See team photo.) Criminal Justice and Behavior 37:1278-1300, 2010. {Criminology}
S. Richardson, L. Bottolo, and J.S. Rosenthal, Bayesian models for sparse regression analysis of high dimensional data [in pdf only]. (Published in Valencia IX Bayesian Meeting conference proceedings, 2011.)
J. Chen and J.S. Rosenthal, Decrypting Classical Cipher Text Using Markov Chain Monte Carlo [or in pdf or published version]. (See also the related software.) Stat. and Comput. 22:397-413, 2011. {Computer Science}
M.A. Turner, J.S. Rosenthal, J. Chen, and C. Hao, Adaption to Climate Change: Evidence from 18th and 19th Century Iceland [in pdf only]. Adv. Appl. Stat. 28:77-108, 2012. (See also the conference proceedings version in AER P&P 102:1-8, 2012.) {Climate Science}
D.M. Day, J.D. Nielsen, A.K. Ward, Y. Sun, J.S. Rosenthal, T. Duchesne, I. Bevc, and L. Rossman, Long-term Follow-up of Criminal Activity with Adjudicated Youth in Ontario [in pdf only]. Canadian J. Criminology and Criminal Justice 54(4):378-413, 2012. {Criminology}

2009:

Y. Atchadé, G.O. Roberts, and J.S. Rosenthal, Towards Optimal Scaling of Metropolis-Coupled Markov Chain Monte Carlo [or in pdf]. See also my slightly-related Cambridge talk. (Stat. and Comput. 21:555-568, 2011.)
M.A. Proschan and J.S. Rosenthal, Beyond the Quintessential Quincunx [in pdf only]. The American Statistician 64:78-82, 2010. (See also the related Java applet.)
J.S. Rosenthal and A.H. Yoon, Detecting Multiple Authorship of United States Supreme Court Legal Decisions Using Function Words [or in pdf]. (See also the related software.) Ann. Appl. Stat. 5:283-308, 2011. (See the published version.) {Law}

2008:

G.O. Roberts and J.S. Rosenthal, Quantitative Non-Geometric Convergence Bounds for Independence Samplers [or in pdf]. MCAP 13:391-403, 2011.
J.S. Rosenthal, Optimal Proposal Distributions and Adaptive MCMC [or in pdf]. (Chapter 4 of Handbook of MCMC, 2011 [amazon.ca, amazon.com]. See also the related software.)
J.S. Rosenthal, Optimising Monte Carlo Search Strategies for Automated Pattern Detection [or in pdf]. Far East J. Math. Sci. 32:311-328, 2009. (See also the related computer vision Java applet.) {Computer Science}
Y. Bai, G.O. Roberts, and J.S. Rosenthal, On the Containment Condition for Adaptive Markov Chain Monte Carlo Algorithms [or in pdf]. (Significantly revised and expanded, July 2010; see the previous version [or in pdf]). Adv. Appl. Stat. 21:1-54, 2011.
R.V. Craiu, J.S. Rosenthal, and Chao Yang, Learn From Thy Neighbor: Parallel-Chain and Regional Adaptive MCMC [or in pdf]. (JASA 488:1454-1466, 2009.)
J.S. Rosenthal, A mathematical analysis of the Sleeping Beauty problem [or in pdf]. Math. Intel. 31:32-37, 2009. {Philosophy}
D.M. Day, I. Bevc, F. Theodor, J.S. Rosenthal, and T. Duchesne, Change and Continuity in Criminal Offending: Criminal Trajectories of the 'Toronto' Sample. (Unpublished report written for the Ontario Ministry of Children and Youth Services.) {Criminology}
J.S. Rosenthal, Markov Chain Monte Carlo Algorithms: Theory and Practice [or in pdf]. (For MCQMC'08 conference proceedings.)

2007:

O. Häggström and J.S. Rosenthal, On Variance Conditions for Markov Chain CLTs [or in pdf, published, online]. (Elec. Comm. Prob. 12:454-464, 2007.)
M. Bedard and J.S. Rosenthal, Optimal Scaling of Metropolis Algorithms: Heading Towards General Target Distributions [or in pdf]. (Can. J. Stat. 36(4):483-503, 2008.)
J.P. Hobert and J.S. Rosenthal, Norm Comparisons for Data Augmentation [or in pdf]. (Adv. Appl. Stat. 7:291-302, 2007.)
J.S. Rosenthal, AMCMC: An R interface for adaptive MCMC [or in pdf, or published version]. (See also the related software.) (Comp. Stat. & Data Anal. 51:5467-5470, 2007.)
J.S. Rosenthal, Expressions for the Markov Chain CLT Variance [or in pdf]. (See also the earlier version.) [Unpublished notes, superceded by this paper.]
J.S. Rosenthal, Waiting time correlations on disorderly streetcar routes [or in pdf]. (See also the related software.) (Int. J. Pure Appl. Math. Sci., to appear.) {Transportation Theory}
D.M. Day, I. Bevc, T. Duchesne, J.S. Rosenthal, Y. Sun, and F. Theodor (2007), Criminal trajectories from adolescence to adulthood in an Ontario sample of offenders. (Proc. 2007 North American Correctional and Criminal Justice Psych. Conf., 143-148.) {Criminology}

2006:

G.O. Roberts and J.S. Rosenthal, Variance bounding Markov chains [or in pdf or published version]. (Ann. Appl. Prob. 18:1201-1214, 2008.)
G.O. Roberts, J.S. Rosenthal, J. Segers, and B. Sousa, Extremal Indices, Geometric Ergodicity of Markov Chains, and MCMC [or in pdf]. (Extremes 9:213-229, 2006.)
G.O. Roberts and J.S. Rosenthal, Examples of Adaptive MCMC [or in pdf]. (See also the related software, a related talk and talk#2 and French-language talk, and this follow-up paper.) (J. Comp. Graph. Stat. 18:349-367, 2009.)

2005:

G.O. Roberts and J.S. Rosenthal, Coupling and Ergodicity of Adaptive MCMC [or in pdf]. (See also the related Java applet and related French-language abstract.) (J. Appl. Prob. 44:458-475, 2007.)
D.M. Day, I. Bevc, T. Duchesne, J.S. Rosenthal, L. Rossman, and F. Theodor, Comparison of Adult Offense Prediction Methods based on Juvenile Offense Trajectories using Cross-Validation [or in pdf] (Adv. Appl. Stat. 7:1-46, 2007). {Criminology}

2004:

G.O. Roberts and J.S. Rosenthal, Harris Recurrence of Metropolis-Within-Gibbs and Trans-Dimensional Markov Chains [or in pdf]. (Ann. Appl. Prob. 16:2123-2139, 2006.)
G.O. Roberts and J.S. Rosenthal, General state space Markov chains and MCMC algorithms [or in pdf / arXiv / journal]. (Probability Surveys 1:20-71, 2004.) [See also related follow-up papers here and here and here and here and here.]
M. Bramson, J. Quastel, and J.S. Rosenthal, When Can Martingales Avoid Ruin? [or in pdf]. (Unpublished manuscript.)

2003:

D.M. Day, I. Bevc, J.S. Rosenthal, T. Duchesne, L. Rossman, and F. Theodor, Predicting Adult Offenders' Criminal Trajectories From Their Juvenile Criminal Trajectories. (Poster, American Psychological Association annual convention, 2003.)
I. Bevc, T. Duchesne, J.S. Rosenthal, L. Rossman, F. Theodor, and E. Sowa, Young Offenders' Diagnoses As Predictors of Subsequent Adult Criminal Behaviour. (Poster, American Psychological Association annual convention, 2003.) {Criminology}
Y.F. Atchadé and J.S. Rosenthal, On Adaptive Markov Chain Monte Carlo Algorithms [or in pdf]. (See also the related Java applet.) (Bernoulli 11:815-828, 2005.)
G.O. Roberts and J.S. Rosenthal, Downweighting Tightly Knit Communities in World Wide Web Rankings [or in pdf] (Adv. Appl. Stat. 3:199-216, 2003.) {Computer Science}
O.F. Christensen, G.O. Roberts, and J.S. Rosenthal, Scaling Limits for the Transient Phase of Local Metropolis-Hastings Algorithms [or in pdf]. (JRSSB 67:253-268, 2005.)

2002:

A. Feuerverger and J.S. Rosenthal, Achieving Limiting Distributions for Markov Chains Using Back Buttons [or in pdf]. (Stat. and Comput. 14:131-141, 2004. See also the extended abstract version and the related C program.) {Computer Science}
S.P. Brooks, Y. Fan, and J.S. Rosenthal, Perfect Forward Simulation via Simulated Tempering [or pdf]. (Comm. Stat.: Sim. and Comp. 35:683-713, 2006.) See also the related computer code.
J.S. Rosenthal, Geometric Convergence Rates for Time-Sampled Markov Chains [or in pdf]. (J. Theoretical Prob. 16:671-688, 2003.)
R. Douc, E. Moulines, and J.S. Rosenthal, Quantitative bounds on convergence of time-inhomogeneous Markov Chains [or in pdf]. (Ann. Appl. Prob. 14:1643-1665, 2004.)
J.S. Rosenthal, Quantitative convergence rates of Markov chains: A simple account [or in pdf]. (See also a related French-language abstract.) (Elec. Comm. Prob. 7 no. 13:123-128, 2002.)
T. Duchesne and J.S. Rosenthal, On the Collapsibility of Lifetime Regression Models [or in pdf]. (Adv. Appl. Prob. 35:755-772, 2003.) (See also the conference proceedings version.)

2001:

G. Fort, E. Moulines, G.O. Roberts, and J.S. Rosenthal, On the geometric ergodicity of hybrid samplers [or pdf]. (J. Appl. Prob. 40:123-146, 2003.)
G.O. Roberts and J.S. Rosenthal, One-shot coupling for certain stochastic recursive sequences [or in pdf]. (Stoch. Proc. Appl. 99:195-208, 2002.)
G.O. Roberts and J.S. Rosenthal, Combinatorial identities associated with CFTP [or in pdf]. (See also the related C program.) Far East J. Math. Sci. 13:391-404, 2004.
G.O. Roberts and J.S. Rosenthal, Optimal scaling for various Metropolis-Hastings algorithms [or in pdf]. (Statistical Science 16:351-367, 2001.)
J.S. Rosenthal, Asymptotic Variance and Convergence Rates of Nearly-Periodic MCMC Algorithms [or in pdf]. (JASA 98:169-177, 2003.) (See also the original, longer version [or in pdf] and the follow-up paper [or in pdf].)
J.P. Hobert, G.L. Jones, B. Presnell, and J.S. Rosenthal, On the Applicability of Regenerative Simulation in Markov Chain Monte Carlo [or pdf]. (Biometrika 89:731-743, 2002.)

2000:

G.O. Roberts and J.S. Rosenthal, Small and pseudo-small sets for Markov chains [or in pdf]. (Stochastic Models 17:121-145, 2001.)
J.J. Lu, J.S. Rosenthal, and A.E. Shaffer, A case study in the meta-reasoning procedure ND [or pdf]. (J. Exp. Th. Artificial Intelligence 15:47-71, 2003.) (See also the conference proceedings version in FTP'2000.) {Computer Science}
L. Breyer, G.O. Roberts, and J.S. Rosenthal, A note on geometric ergodicity and floating-point roundoff error [or in pdf]. (Shortened version [or in pdf] published in Stat. Prob. Lett. 53:123-127, 2001.)
M.J. Gordon and J.S. Rosenthal, Capitalism's Growth Imperative [pdf, published]. Cambridge J. Economics 27:25-48, 2003. {Economics}
A. Borodin, G.O. Roberts, J.S. Rosenthal, and P. Tsaparas, Link Analysis Ranking: Algorithms, Theory, and Experiments [or in pdf]. (ACM TOIT 5:231-297, 2005.) (See also the conference proceedings version, published in WWW10, 2001, chosen as selected area highlight.) {Computer Science}

1999:

R.B. Israel, J.S. Rosenthal, and J.Z. Wei, Finding generators for Markov chains via empirical transition matrices, with applications to credit ratings [or in pdf]. (Mathematical Finance 11:245-265, 2000.) {Economics}
G.O. Roberts and J.S. Rosenthal, Bayesian models with infinite hierarchies [or in pdf]. (Bernoulli 7:453-471, 2001.)
G.O. Roberts and J.S. Rosenthal, Recent progress on computable bounds and the simple slice sampler [or in pdf]. See also the Fields-format version. (In Monte Carlo Methods (N. Madras, ed.), 2000, 123-130.)
G.O. Roberts and J.S. Rosenthal, The polar slice sampler [or in pdf]. (Stochastic Models 18:257-280, 2002.) See also the related French-language slides (or in pdf) and Java applet.
J.S. Rosenthal, Parallel computing and Monte Carlo algorithms [or in pdf]. (Far East J. Theor. Stat. 4:207-236, 2000.) See also the related software.
J.S. Rosenthal, A review of asymptotic convergence for general state space Markov chains [or in pdf]. (Expository paper. Far East J. Theor. Stat. 5:37-50, 2001.)

1998:

G.O. Roberts and J.S. Rosenthal, Markov chains and de-initialising processes [or in pdf] [formerly Sufficient Markov chains]. (Scandanavian J. Stat. 28:489-504, 2001.)
R. Pemantle and J.S. Rosenthal, Moment conditions for a sequence with negative drift to be uniformly bounded in L^r [or in pdf]. (Stoch. Proc. Appl. 82:143-155, 1999.)
J.A. Fill, M. Machida, D.J. Murdoch, and J.S. Rosenthal, Extension of Fill's perfect rejection sampling algorithm to general chains [or in pdf]. (Random Structures and Algorithms 17:290-316, 2000.) See also the extended abstract version [or in pdf] (in Monte Carlo Methods (N. Madras, ed.), 2000, 37-52) and the original two-author version [or in pdf].
D.J. Murdoch and J.S. Rosenthal, Efficient use of exact samples [or in pdf]. (Stat. and Comput. 10:237-243, 2000.) See also the associated poster, the related Java applet, and D.B. Wilson's annotated bibliography.
M.J. Osborne, J.S. Rosenthal, and M.A. Turner, Meetings with costly participation [or pdf]. (American Economic Review 90:927-943, 2000.) (See also Osborne's expository article.) {Game Theory}
S. Petrone, G.O. Roberts, and J.S. Rosenthal, A note on convergence rates of Gibbs sampling for nonparametric mixtures [or in pdf]. (Far East J. Theor. Stat. 3:213-225, 1999.)

1997:

M.K. Cowles, G.O. Roberts, and J.S. Rosenthal, Possible biases induced by MCMC convergence diagnostics [or in pdf]. (J. Stat. Comp. and Sim. 64:87-104, 1999.)
G.O. Roberts and J.S. Rosenthal, Convergence of slice sampler Markov chains [or in pdf]. (JRSSB 61:643-660 , 1999.) See also the related Java applet.
G.O. Roberts and J.S. Rosenthal, On convergence rates of Gibbs samplers for uniform distributions [or in pdf]. (Ann. Appl. Prob. 8:1291-1302, 1998.)
J.S. Rosenthal and P.O. Schwartz, Gambling systems and multiplication-invariant measures [or in pdf]. (Adv. Appl. Math. 22:303-311, 1999.)
G.O. Roberts and J.S. Rosenthal, Markov chain Monte Carlo: Some practical implications of theoretical results [or in pdf]. (Can. J. Stat. 26:5-31, 1998, with discussion and rejoinder [or in pdf].) See also the related Java applet and related talk [or in pdf].
G.O. Roberts and J.S. Rosenthal, Two convergence properties of hybrid samplers [or in pdf]. (Ann. Appl. Prob. 8:397-407, 1998.)

1996:

G.O. Roberts and J.S. Rosenthal, Geometric ergodicity and hybrid Markov chains [or in pdf]. (Elec. Comm. Prob. 2, paper 2, 1997.)
M.K. Cowles and J.S. Rosenthal, A simulation approach to convergence rates for Markov chain Monte Carlo algorithms [or in pdf]. (Stat. and Comput. 8:115-124, 1998.)
G.O. Roberts and J.S. Rosenthal, Quantitative bounds for convergence rates of continuous time Markov processes [or in pdf]. (Elec. J. Prob. 1, paper 9, 1996.)

1995:

G.O. Roberts, J.S. Rosenthal, and P.O. Schwartz, Convergence properties of perturbed Markov chains [or in pdf]. (J. Appl. Prob. 35:1-11, 1998.)
G.O. Roberts and J.S. Rosenthal, Optimal scaling of discrete approximations to Langevin diffusions [or in pdf]. (JRSSB 60:255-268, 1998.)
J.S. Rosenthal, Faithful couplings of Markov chains: now equals forever [or in pdf]. (Adv. Appl. Math. 18:372-381, 1997.)

1994:

G.O. Roberts and J.S. Rosenthal, Shift-coupling and convergence rates of ergodic averages [or in pdf]. (Comm. in Stat. - Stoch. Models 13:147-165, 1997.) (See also the published version.)
J.S. Rosenthal, Markov chain convergence: from finite to infinite [or in pdf]. (Stoch. Proc. Appl. 62:55-72, 1996.)
J.S. Rosenthal, Analysis of the Gibbs Sampler for a model related to James-Stein Estimators [or in pdf]. (Stat. and Comput. 6:269-275, 1996.)
J.R. Baxter and J.S. Rosenthal, Rates of convergence for everywhere-positive Markov chains [or in pdf]. (Stat. Prob. Lett. 22:333-338, 1995.)

1993:

J.S. Rosenthal, Minorization Conditions and Convergence Rates for Markov Chain Monte Carlo [or in pdf]. (JASA 90:558-566, 1995.) See also the one-page supplement [or in pdf].
J.R. Hoffman and J.S. Rosenthal, Convergence of Independent Particle Systems [or in pdf]. (Stoch. Proc. Appl. 56:295-305, 1995.)
J.S. Rosenthal, Convergence rates of Markov chains [or in pdf]. (Expository paper. SIAM Review 37:387-405, 1995.) (See also a clarification [or postscript], and an older version including exercises [or in postscript].)
J.S. Rosenthal, Active-Learning Strategies in Advanced Mathematics Classes [or in pdf]. (Education paper. Studies in Higher Ed. 20:223-228, 1995.) {Education}

1992:

J.S. Rosenthal, On Generalizing the Cut-off Phenomenon for Random Walks on Groups [or in pdf]. (Adv. Appl. Math. 16:306-320, 1995.)
J.S. Rosenthal, On Duality of Probabilities for Card-dealing [or in pdf]. (Proc. AMS 123:559-561, 1995.)
J.S. Rosenthal, Random Rotations: Characters and Random Walks on SO(N) [or in pdf]. (Ann. Prob. 22:398-423, 1994.) [From my Ph.D. thesis.]
J.S. Rosenthal, Random Walks on Discrete and Continuous Circles [or in pdf]. (J. Appl. Prob. 30:780-789, 1993.) [From my Ph.D. thesis.]
J.S. Rosenthal, Rates of Convergence for Data Augmentation on Finite Sample Spaces [or in pdf]. (Ann. Appl. Prob. 3:819-839, 1993.) [From my Ph.D. thesis.]
J.S. Rosenthal, Rates of Convergence for Gibbs Sampling for Variance Components Models [or in pdf]. (Ann. Stat. 23:740-761, 1995.) [From my Ph.D. thesis.]
J.S. Rosenthal, Convergence of pseudo-finite Markov chains [or in pdf]. (Unpublished manuscript.)

1989:

M.D. Choi, J.S. Rosenthal, and P. Rosenthal, Linear-Algebraic Results Associated with Antiferromagnetic Heisenberg Chains [or in pdf]. (SIAM J. Matrix Anal. Appl. 3:830-852, 1993.) {Physics}

Books:

J.S. Rosenthal, A First Look at Stochastic Processes (advanced-undergraduate textbook). World Scientific Publishing Co., 202 pages, 2019. (See also the related Javascript simulations.)
J.S. Rosenthal, Knock on Wood: Luck, Chance, and the Meaning of Everything (general-public book). HarperCollins Canada, 333 pages, 2018.
J.S. Rosenthal, Struck by Lightning: The Curious World of Probabilities (general-public book). HarperCollins Canada, 272 pages, 2005. (Later published in many other countries too.)
M.J. Evans and J.S. Rosenthal, Probability and Statistics: The Science of Uncertainty (undergraduate textbook). W.H. Freeman and Co., 685 pages, 2003. (Now available for free in pdf format!)
J.S. Rosenthal, A First Look at Rigorous Probability Theory (graduate textbook). World Scientific Publishing Co., 177 pages, 2000. Second edition, 219 pages, 2006.

Other Research-Related Writings:

J.S. Rosenthal's Ph.D. thesis, Rates of Convergence for Gibbs Sampler and other Markov Chains, 1992. See acknowledgements, front matter, introduction, chapter 2, chapter 3, chapter 4, chapter 5, conclusion, citation, and math genealogy (source).
J.S. Rosenthal, Theoretical rates of convergence for Markov chain Monte Carlo [or in pdf]. (Interface '94 conference proceedings.)
J.S. Rosenthal, The de Branges proof of the Bieberbach conjecture [or in pdf]. (Master's thesis, 1990.)
U. Porod and J.S. Rosenthal, An open problem related to random walks on U(N) [or in pdf] (including prize offer!) and some related notes [or in pdf], 1994.
G.O. Roberts and J.S. Rosenthal, Markov chain Monte Carlo [or in pdf]. A short review article for Section 10 (Probability Theory) of the Encyclopedia of the Actuarial Sciences (S. Asmussen, ed.), 2003.
G.O. Roberts and J.S. Rosenthal, Understanding MCMC [or pdf] (slides for week-long U.K. post-graduate course), 2003. See also the exercises [or in pdf] and solutions [or in pdf] and computer lab [or in pdf] and R commands, and some photos.
J.S. Rosenthal, Statistics and MCMC [or pdf] (slides for survey talk at Markov Chains symposium in Durham, U.K.), 2003.
See also my non-research writings, and my C.V. in postscript / pdf.

Miscellaneous Items of Possible Interest:

I have written some Java applets and Javascript related to my research; see also my computing page and my interdisciplinary research page.
In 2019 I was appointed as a PI of the Fujitsu Co-Creation Research Laboratory, and was also appointed as a Vector Institute Faculty Affiliate.
For the three-year period 2007-2009, I was an Associate Editor of the Canadian Journal of Statistics and of the Electronic Journal of Statistics.
I have been a Supreme Court expert witness (2011; par. 62) and an expert witness in criminal case (2017; par. 18-25, 32) (see related talk / French).
See also my Mathematics Genealogy Project page (from which I constructed my personal math genealogy), and my MathSciNet listings, and my Google Scholar listings.
Thanks to P. Kim and J.Y. Koo for christening the "Rosenthal distribution" in this paper (J. Mult. Anal. 80:21-42, 2002)!
For research papers by others about similar topics, visit the MCMC Preprint Service, and the exact sampling annotated bibliography.
My Erdos number is computed to be 3, thanks to: Bruce A. Reznick (1) and Man-Duen Choi (2); or alternatively Svante Janson (1) and Robin Pemantle (2).
For another take on probability theory, check out this Simpsons transcript.
I am a very serious researcher. Here I am hard at work in Cambridge, England; in Tirano, Italy; in Monte Carlo, Monaco; in Ottawa, Canada; in Lancaster, England; in Bormio, Italy (with an audience); and in Hamilton Island, Australia (with more audience and on a boat).

[Jeffrey Rosenthal's Home Page / contact info]