DOCSLIB.ORG

JEROME P. REITER Department of Statistical Science, Duke University Box 90251, Durham, NC 27708 Phone: 919 668 5227

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
JEROME P. REITER Department of Statistical Science, Duke University Box 90251, Durham, NC 27708 Phone: 919 668 5227 JEROME P. REITER Department of Statistical Science, Duke University Box 90251, Durham, NC 27708 phone: 919 668 5227. email: [email protected]. September 26, 2021 EDUCATION Ph.D. in Statistics, Harvard University, 1999. A.M. in Statistics, Harvard University, 1996. B.S. in Mathematics, Duke University, 1992. DISSERTATION \Estimation in the Presence of Constraints that Prohibit Explicit Data Pooling." Advisor: Donald B. Rubin. POSITIONS Academic Appointments Professor of Statistical Science and Bass Fellow, Duke University, 2015 - present. Mrs. Alexander Hehmeyer Professor of Statistical Science, Duke University, 2013 - 2015. Mrs. Alexander Hehmeyer Associate Professor of Statistical Science, Duke University, 2010 - 2013. Associate Professor of Statistical Science, Duke University, 2009 - 2010. Assistant Professor of Statistical Science, Duke University, 2006 - 2008. Assistant Professor of the Practice of Statistics and Decision Sciences, Duke University, 2002 - 2006. Lecturer in Statistics, University of California at Santa Barbara, 2001 - 2002. Assistant Professor of Statistics, Williams College, 1999 - 2001. Other Appointments Chair, Department of Statistical Science, Duke University, 2019 - present. Associate Chair, Department of Statistical Science, Duke University, 2016 - 2019. Mathematical Statistician (part-time), U. S. Bureau of the Census, 2015 - present. Associate/Deputy Director of Information Initiative at Duke, Duke University, 2013 - 2019. Social Sciences Research Institute Data Services Core Director, Duke University, 2010 - 2013. Interim Director, Triangle Research Data Center, 2006. Senior Fellow, National Institute of Statistical Sciences, 2002 - 2005. 1 ACADEMIC HONORS Keynote talk, 11th Official Statistics and Methodology Symposium (Statistics Korea), 2021. Fellow of the Institute of Mathematical Statistics, 2020. Clifford C. Clogg Memorial Lecture, Pennsylvania State University, 2020 (postponed due to covid-19). MIDS Distinguished Faculty Award, Duke University, 2020. Outstanding Postdoc Mentor Award, Duke University, 2016. Plenary talk, International Conference on Advances in Interdisciplinary Statistics and Com- binatorics, 2016. Gertrude M. Cox Award, 2014. W. J. Youden Award in Interlaboratory Testing, 2013. Plenary talk, UNC-Greensboro Regional Mathematics and Statistics Conference, 2013. Plenary talk, Political Methodology XII Conference, 2012. Fellow of the American Statistical Association, 2011. Bass Chair for Excellence in Undergraduate Teaching and Research, Duke University, 2010 - 2015. Cathie Marsh Fellowship, Centre for Census and Survey Research, University of Manchester, 2010. Elected member of International Statistical Institute, 2007. Alumni Distinguished Undergraduate Teaching Award, Duke University, 2007. GRANTS AND FUNDED RESEARCH Duke Population Research Center, \Linking the ChIRDU Participants to InfoUSA Data," 7/2021 - 12/2022, $26,000. Role: Principal Investigator. National Institutes of Health, \Duke Population Research Center," 6/2020 - 5/2025, $2,746,506. Role: Co-investigator. National Science Foundation (MMS), \Leveraging Auxiliary Information on Marginal Distri- butions in Multiple Imputation for Survey Nonresponse," 9/2017 - 8/2020, $300,000. Role: Principal Investigator. National Science Foundation (NCRN), \The Triangle Census Research Network: Supplemen- tal Award 3," 10/2016 - 9/2018, $568,015. Role: Principal Investigator. Alfred P. Sloan Foundation, \Computational Methods and Tools for Creating High Quality Household Microdata", 1/2016 - 7/2017, $108,903. Role: Principal Investigator. 2 National Science Foundation (DIBBs), \An Integrated System for Public/Private Access to Large-Scale, Confidential Social Science Data," 1/2015 - 12/2018, $1,498,683. Role: Principal Investigator. Duke University Energy Initiative Seed Grant, \Data Development for Measuring the Impact of Energy Efficiency Assessments Linking the DOE Industrial Assessment Center Database to the U. S. Census of Manufactures," 9/2013 - 9/2015, $30,000. Role: Co-investigator. National Science Foundation (NCRN), \The Triangle Census Research Network: Supplemen- tal Award 2," 10/2013 - 9/2018, $199,737. Role: Principal Investigator. National Science Foundation (NCRN), \The Triangle Census Research Network: Supplemen- tal Award 1," 10/2012 - 9/2018, $322,027. Role: Principal Investigator. U.S. Bureau of the Census, \Creating a Synthetic Public Use File for the Longitudinal Busi- ness Database," 9/2012 - 9/2014, $117,919 plus $30,000 discount on Duke's costs for Triangle Census Research Data Center. Role: PI on Intergovernmental Personnel Agreement. National Science Foundation (NCRN-RCN), \Coordination of the NSF-Census Research Net- work," 7/2012 - 6/2017, $748,577 total, $0 to Duke. Role: Co-Investigator (PI: Alan Karr). National Science Foundation (NCRN), \The Triangle Census Research Network," 10/2011 - 9/2018, $2,997,591 total, $2,144,766 to Duke. Role: Principal Investigator. National Science Foundation (MMS), \Multiple Imputation Methods for Handling Missing Data in Panel Studies with Refreshment Samples," 6/2011 - 5/2014, $160,000. Role: Principal Investigator. U.S. Bureau of the Census, \Creating a Synthetic Public Use File for the Longitudinal Busi- ness Database," 9/2010 - 9/2012, $95,828 plus $30,000 discount on Duke's costs for Triangle Census Research Data Center. Role: PI on Intergovernmental Personnel Agreement. National Science Foundation (TC): \Large: Collaborative Research: Practical Privacy: Met- rics and Methods for Protecting Record-level and Relational Data," 7/2010 - 7/2015, $583,169. Role: Principal Investigator. National Science Foundation (SES): \Joint NSF-Census-IRS Workshop on synthetic data and confidentiality protection," 7/2009 - 6/2010, $18,480. Role: Co-Investigator. National Institutes of Health (NIA): \R21: Sharing Confidential Datasets With Geographic Identifiers Via Multiple Imputation," 3/2009 - 1/2011, $351,780. Role: Principal Investigator. National Science Foundation (MMS), \Methodology for Improving Public Use Data Dissem- ination Via Multiply-Imputed, Partially Synthetic Data," 6/2008 - 5/2011, $180,000. Role: Principal Investigator. Environmental Protection Agency, \Southern Center for Environmentally Driven Disparities in Birth Outcomes," 5/2007 - 5/2011, $7,735,620. Role: Co-Investigator (PI: Marie Lynn Miranda). National Institutes of Health (NIDA), \The Alcohol Pharmacology Education Partnership," 8/2005 - 7/2010, $1,250,000. Role: Co-investigator (PI: Rochelle Schwartz-Bloom). 3 National Science Foundation (ITR), \Information Technology Challenges for Secure Access to Confidential Social Science Data," 10/2004 - 10/2008, $2,938,000 total, $247,903 to Duke. Role: Senior Scientist (PI: John Abowd). U.S. Bureau of the Census, \Using Synthetic Data to Protect Confidentiality of People in Group Quarters in the American Community Survey," 9/2005 - 9/2007, $24,000. Role: Prin- cipal Investigator. U.S. Bureau of the Census, \Synthetic Data Methods for the Survey of Income and Program Participation Public Use File," 6/2005 - 6/2006, $25,000. Role: Principal Investigator. U.S. Bureau of the Census, \Assessing Disclosure Risks for Remote Access Model Servers," 6/2004 - 7/2005, $25,000. Role: Principal Investigator. Transportation Research Board, 2005. Commissioned to write paper on threats to data confidentiality in public-use transportation data (with David Banks), $10,000. National Institute of Statistical Sciences, \Data Confidentiality, Data Quality, and Data In- tegration for Federal Databases: Foundations to Software Prototypes," 8/2002 - 8/2004, $25,000. Role: Senior Fellow. National Academy of Sciences Panel on Confidential Data Access for Research Purposes, 2003. Commissioned to write paper on measuring disclosure risks, $5,000. U.S. Bureau of the Census, \Research on Synthetic Data," 8/2002 - 8/2003, $16,000. Role: Principal Investigator. PROFESSIONAL SERVICE Editorial Appointments Editor, Administrative Records for Survey Methodology, book published by John Wiley & Sons, Inc., 2021. Editor, Statistics and Public Policy, 2019 - present. Guest Editor, PNAS, 2020. Guest Editor, Statistical Science, 2018. Editorial Board, Transactions on Data Privacy, 2013 - 2019. Associate Editor, Journal of Privacy and Confidentiality, 2006 - 2017. Associate Editor, Survey Methodology, 2004 - 2013. Associate Editor, Journal of Statistical Theory and Practice, 2009 - 2013. Associate Editor, Journal of the American Statistical Association, 2006 - 2013. Advisory Board, The Encyclopedia of Measurement and Statistics, 2005. Membership on National Academy of Science Committees, Panels, and Expert Meetings Expert Meetings on Census 2020 Disclosure Avoidance System, 2020 - present. Committee on National Statistics, 2017 - present. Committee on 7th Edition of Principles and Practices for a Federal Statistical Agency, 2020 - 2021. 4 Standing Committee on Creating the American Opportunity Study | Phase 1, 2015 - 2017. BEA Expert Meeting on Exploiting Commercial Data for Official Economic Statistics, 2015. Panel on Addressing Priority Technical Issues for the Next Decade of the American Community Survey, 2012 - 2015. Committee on Long-Term Stewardship of Safety Data from the Second Strategic High- way Research Program, 2012 - 2013. Expert Meeting on Redaction Strategy for the Airline Pilots Safety Data, 2008. Panel on Collecting, Storing, Accessing, and Protecting Social Survey Data Containing Biological Measures, 2008 - 2010. Panel on Re-engineering the Survey of Income and Program Participation, 2006 -
Load more

Recommended publications
  • Report on Statistical Disclosure Limitation Methodology
    STATISTICAL POLICY WORKING PAPER 22 (Second version, 2005) Report on Statistical Disclosure Limitation Methodology Federal Committee on Statistical Methodology Originally Prepared by Subcommittee on Disclosure Limitation Methodology 1994 Revised by Confidentiality and Data Access Committee 2005 Statistical and Science Policy Office of Information and Regulatory Affairs Office of Management and Budget December 2005 The Federal Committee on Statistical Methodology (December 2005) Members Brian A. Harris-Kojetin, Chair, Office of William Iwig, National Agricultural Management and Budget Statistics Service Wendy L. Alvey, Secretary, U.S. Census Arthur Kennickell, Federal Reserve Board Bureau Nancy J. Kirkendall, Energy Information Lynda Carlson, National Science Administration Foundation Susan Schechter, Office of Management and Steven B. Cohen, Agency for Healthcare Budget Research and Quality Rolf R. Schmitt, Federal Highway Steve H. Cohen, Bureau of Labor Statistics Administration Lawrence H. Cox, National Center for Marilyn Seastrom, National Center for Health Statistics Education Statistics Robert E. Fay, U.S. Census Bureau Monroe G. Sirken, National Center for Health Statistics Ronald Fecso, National Science Foundation Nancy L. Spruill, Department of Defense Dennis Fixler, Bureau of Economic Analysis Clyde Tucker, Bureau of Labor Statistics Gerald Gates, U.S. Census Bureau Alan R. Tupek, U.S. Census Bureau Barry Graubard, National Cancer Institute G. David Williamson, Centers for Disease Control and Prevention Expert Consultant Robert Groves, University of Michigan and Joint Program in Survey Methodology Preface The Federal Committee on Statistical Methodology (FCSM) was organized by the Office of Management and Budget (OMB) in 1975 to investigate issues of data quality affecting Federal statistics. Members of the committee, selected by OMB on the basis of their individual expertise and interest in statistical methods, serve in a personal capacity rather than as agency representatives.
    [Show full text]
  • The American Statistician
    This article was downloaded by: [T&F Internal Users], [Rob Calver] On: 01 September 2015, At: 02:24 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: 5 Howick Place, London, SW1P 1WG The American Statistician Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/utas20 Reviews of Books and Teaching Materials Published online: 27 Aug 2015. Click for updates To cite this article: (2015) Reviews of Books and Teaching Materials, The American Statistician, 69:3, 244-252, DOI: 10.1080/00031305.2015.1068616 To link to this article: http://dx.doi.org/10.1080/00031305.2015.1068616 PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes.
    [Show full text]
  • Biometrical Applications in Biological Sciences-A Review on the Agony for Their Practical Efficiency- Problems and Perspectives
    Biometrics & Biostatistics International Journal Review Article Open Access Biometrical applications in biological sciences-A review on the agony for their practical efficiency- Problems and perspectives Abstract Volume 7 Issue 5 - 2018 The effect of the three biological sciences- agriculture, environment and medicine S Tzortzios in the people’s life is of the greatest importance. The chain of the influence of the University of Thessaly, Greece environment to the form and quality of the agricultural production and the effect of both of them to the people’s health and welfare consists in an integrated system Correspondence: S Tzortzios, University of Thessaly, Greece, that is the basic substance of the human life. Agriculture has a great importance in Email [email protected] the World’s economy; however, the available resources for research and technology development are limited. Moreover, the environmental and productive conditions are Received: August 12, 2018 | Published: October 05, 2018 very different from one country to another, restricting the generalized transferring of technology. The statistical methods should play a paramount role to insure both the objectivity of the results of agricultural research as well as the optimum usage of the limited resources. An inadequate or improper use of statistical methods may result in wrong conclusions and in misuse of the available resources with important scientific and economic consequences. Many times, Statistics is used as a basis to justify conclusions of research work without considering in advance the suitability of the statistical methods to be used. The obvious question is: What importance do biological researchers give to the statistical methods? The answer is out of any doubt and the fact that most of the results published in specialized journals includes statistical considerations, confirms its importance.
    [Show full text]
  • Visualizing Research Collaboration in Statistical Science: a Scientometric
    University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Library Philosophy and Practice (e-journal) Libraries at University of Nebraska-Lincoln 9-13-2019 Visualizing Research Collaboration in Statistical Science: A Scientometric Perspective Prabir Kumar Das Library, Documentation & Information Science Division, Indian Statistical Institute, 203 B T Road, Kolkata - 700108, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/libphilprac Part of the Library and Information Science Commons Das, Prabir Kumar, "Visualizing Research Collaboration in Statistical Science: A Scientometric Perspective" (2019). Library Philosophy and Practice (e-journal). 3039. https://digitalcommons.unl.edu/libphilprac/3039 Viisualliiziing Research Collllaborattiion iin Sttattiisttiicall Sciience:: A Sciienttomettriic Perspecttiive Prrabiirr Kumarr Das Sciienttiiffiic Assssiissttantt – A Liibrrarry,, Documenttattiion & IInfforrmattiion Sciience Diiviisiion,, IIndiian Sttattiisttiicall IInsttiittutte,, 203,, B.. T.. Road,, Kollkatta – 700108,, IIndiia,, Emaiill:: [email protected] Abstract Using Sankhyā – The Indian Journal of Statistics as a case, present study aims to identify scholarly collaboration pattern of statistical science based on research articles appeared during 2008 to 2017. This is an attempt to visualize and quantify statistical science research collaboration in multiple dimensions by exploring the co-authorship data. It investigates chronological variations of collaboration pattern, nodes and links established among the affiliated institutions and countries of all contributing authors. The study also examines the impact of research collaboration on citation scores. Findings reveal steady influx of statistical publications with clear tendency towards collaborative ventures, of which double-authored publications dominate. Small team of 2 to 3 authors is responsible for production of majority of collaborative research, whereas mega-authored communications are quite low.
    [Show full text]
  • STATISTICAL SCIENCE Volume 35, Number 1 February 2020
    STATISTICAL SCIENCE Volume 35, Number 1 February 2020 Special Issue on Statistics and Science IntroductiontotheSpecialIssue............................................................. 1 Model-Based Approach to the Joint Analysis of Single-Cell Data on Chromatin Accessibility andGeneExpression................Zhixiang Lin, Mahdi Zamanighomi, Timothy Daley, Shining Ma and Wing Hung Wong 2 Risk Models for Breast Cancer and Their Validation . Adam R. Brentnall and Jack Cuzick 14 SomeStatisticalIssuesinClimateScience..................................Michael L. Stein 31 A Tale of Two Parasites: Statistical Modelling to Support Disease Control Programmes in Africa............Peter J. Diggle, Emanuele Giorgi, Julienne Atsame, Sylvie Ntsame Ella, Kisito Ogoussan and Katherine Gass 42 QuantumScienceandQuantumTechnology..................Yazhen Wang and Xinyu Song 51 StatisticalMethodologyinSingle-MoleculeExperiments............Chao Du and S. C. Kou 75 Statistical Molecule Counting in Super-Resolution Fluorescence Microscopy: Towards QuantitativeNanoscopy..........Thomas Staudt, Timo Aspelmeier, Oskar Laitenberger, Claudia Geisler, Alexander Egner and Axel Munk 92 Data Denoising and Post-Denoising Corrections in Single Cell RNA Sequencing ...................................Divyansh Agarwal, Jingshu Wang and Nancy R. Zhang 112 Statistical Inference for the Evolutionary History of Cancer Genomes .....Khanh N. Dinh, Roman Jaksik, Marek Kimmel, Amaury Lambert and Simon Tavaré 129 Maximum Independent Component Analysis with Application to EEG Data ........................................Ruosi
    [Show full text]
  • Causality: Readings in Statistics and Econometrics Hedibert F
    Causality: Readings in Statistics and Econometrics Hedibert F. Lopes, INSPER http://www.hedibert.org/current-teaching/#tab-causality Annotated Bibliography 1 Articles 1. Angrist and Imbens (1995) Two-Stage Least Squares Estimation of Average Causal Effects in Models With Variable Treatment Intensity. JASA, 90, 431-442. 2. Angrist and Krueger (1991) Does compulsory school attendance affect earnings? Quarterly Journal of Economic, 106, 979-1019. 3. Angrist, Imbens and Rubin (1996) Identification of causal effects using instrumental variables (with discussion). JASA, 91, 444-472. 4. Athey and Imbens (2015) Machine Learning Methods for Estimating Heterogeneous Causal Effects. 5. Balke and Pearl (1995). Counterfactuals and policy analysis in structural models. In Besnard and Hanks, Eds., Uncertainty in Artificial Intelligence, Proceedings of the Eleventh Conference. Morgan Kaufmann, San Francisco, 11-18. 6. Bareinboim and Pearl (2015) Causal inference from big data: Theoretical foundations and the data-fusion problem. Proceedings of the National Academy of Sciences. 7. Bollen and Pearl (2013) Eight myths about causality and structural equation models. In Morgan (Ed.) Handbook of Causal Analysis for Social Research, Chapter 15, 301-328. Springer. 8. Bound, Jaeger, and Baker (1995) Problems with Instrumental Variables Estimation when the Correlation Be- tween the Instruments and the Endogenous Regressors is Weak. JASA, 90, 443-450. 9. Brito and Pearl (2002) Generalized instrumental variables. In Darwiche and Friedman, Eds. Uncertainty in Artificial Intelligence, Proceedings of the Eighteenth Conference. Morgan Kaufmann, San Francisco, 85-93. 10. Brzeski, Taddy and raper (2015) Causal Inference in Repeated Observational Studies: A Case Study of eBay Product Releases. arXiv:1509.03940v1. 11. Chambaz, Drouet and Thalabard (2014) Causality, a Trialogue.
    [Show full text]
  • Can P-Values Be Meaningfully Interpreted Without Random Sampling?
    A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Hirschauer, Norbert; Grüner, Sven; Mußhoff, Oliver; Becker, Claudia; Jantsch, Antje Article — Published Version Can p-values be meaningfully interpreted without random sampling? Statistics Surveys Provided in Cooperation with: Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle (Saale) Suggested Citation: Hirschauer, Norbert; Grüner, Sven; Mußhoff, Oliver; Becker, Claudia; Jantsch, Antje (2020) : Can p-values be meaningfully interpreted without random sampling?, Statistics Surveys, ISSN 1935-7516, Cornell University Library, Ithaca, NY, Vol. 14, pp. 71-91, http://dx.doi.org/10.1214/20-SS129 , https://projecteuclid.org/euclid.ssu/1585274548 This Version is available at: http://hdl.handle.net/10419/215709 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle You are not to copy documents for public or commercial Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich purposes, to exhibit the documents publicly, to make them machen, vertreiben oder anderweitig nutzen. publicly available on the internet, or to distribute or otherwise use the documents in public. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, If the documents have been made available under an Open gelten abweichend von diesen Nutzungsbedingungen die in der dort Content Licence (especially Creative Commons Licences), you genannten Lizenz gewährten Nutzungsrechte. may exercise further usage rights as specified in the indicated licence.
    [Show full text]
  • STATISTICAL SCIENCE Volume 36, Number 3 August 2021
    STATISTICAL SCIENCE Volume 36, Number 3 August 2021 Khinchin’s 1929 Paper on Von Mises’ Frequency Theory of Probability . Lukas M. Verburgt 339 A Problem in Forensic Science Highlighting the Differences between the Bayes Factor and LikelihoodRatio...........................Danica M. Ommen and Christopher P. Saunders 344 A Horse Race between the Block Maxima Method and the Peak–over–Threshold Approach ..................................................................Axel Bücher and Chen Zhou 360 A Hybrid Scan Gibbs Sampler for Bayesian Models with Latent Variables ..........................Grant Backlund, James P. Hobert, Yeun Ji Jung and Kshitij Khare 379 Maximum Likelihood Multiple Imputation: Faster Imputations and Consistent Standard ErrorsWithoutPosteriorDraws...............Paul T. von Hippel and Jonathan W. Bartlett 400 RandomMatrixTheoryandItsApplications.............................Alan Julian Izenman 421 The GENIUS Approach to Robust Mendelian Randomization Inference .....................................Eric Tchetgen Tchetgen, BaoLuo Sun and Stefan Walter 443 AGeneralFrameworkfortheAnalysisofAdaptiveExperiments............Ian C. Marschner 465 Statistical Science [ISSN 0883-4237 (print); ISSN 2168-8745 (online)], Volume 36, Number 3, August 2021. Published quarterly by the Institute of Mathematical Statistics, 9760 Smith Road, Waite Hill, Ohio 44094, USA. Periodicals postage paid at Cleveland, Ohio and at additional mailing offices. POSTMASTER: Send address changes to Statistical Science, Institute of Mathematical Statistics, Dues and Subscriptions Office, PO Box 729, Middletown, Maryland 21769, USA. Copyright © 2021 by the Institute of Mathematical Statistics Printed in the United States of America Statistical Science Volume 36, Number 3 (339–492) August 2021 Volume 36 Number 3 August 2021 Khinchin’s 1929 Paper on Von Mises’ Frequency Theory of Probability Lukas M. Verburgt A Problem in Forensic Science Highlighting the Differences between the Bayes Factor and Likelihood Ratio Danica M.
    [Show full text]
  • Statistical Inference Bibliography 1920-Present 1. Pearson, K
    StatisticalInferenceBiblio.doc © 2006, Timothy G. Gregoire, Yale University http://www.yale.edu/forestry/gregoire/downloads/stats/StatisticalInferenceBiblio.pdf Last revised: July 2006 Statistical Inference Bibliography 1920-Present 1. Pearson, K. (1920) “The Fundamental Problem in Practical Statistics.” Biometrika, 13(1): 1- 16. 2. Edgeworth, F.Y. (1921) “Molecular Statistics.” Journal of the Royal Statistical Society, 84(1): 71-89. 3. Fisher, R. A. (1922) “On the Mathematical Foundations of Theoretical Statistics.” Philosophical Transactions of the Royal Society of London, Series A, Containing Papers of a Mathematical or Physical Character, 222: 309-268. 4. Neyman, J. and E. S. Pearson. (1928) “On the Use and Interpretation of Certain Test Criteria for Purposes of Statistical Inference: Part I.” Biometrika, 20A(1/2): 175-240. 5. Fisher, R. A. (1933) “The Concepts of Inverse Probability and Fiducial Probability Referring to Unknown Parameters.” Proceedings of the Royal Society of London, Series A, Containing Papers of Mathematical and Physical Character, 139(838): 343-348. 6. Fisher, R. A. (1935) “The Logic of Inductive Inference.” Journal of the Royal Statistical Society, 98(1): 39-82. 7. Fisher, R. A. (1936) “Uncertain inference.” Proceedings of the American Academy of Arts and Sciences, 71: 245-258. 8. Berkson, J. (1942) “Tests of Significance Considered as Evidence.” Journal of the American Statistical Association, 37(219): 325-335. 9. Barnard, G. A. (1949) “Statistical Inference.” Journal of the Royal Statistical Society, Series B (Methodological), 11(2): 115-149. 10. Fisher, R. (1955) “Statistical Methods and Scientific Induction.” Journal of the Royal Statistical Society, Series B (Methodological), 17(1): 69-78.
    [Show full text]
  • RABI BHATTACHARYA the Department of Mathematics the University of Arizona 617 N Santa Rita Tucson, AZ 85721
    RABI BHATTACHARYA The Department of Mathematics The University of Arizona 617 N Santa Rita Tucson, AZ 85721. 1. Degrees Ph.D. (Statistics) University of Chicago, 1967. 2. Positions Held: Regular Positions 1967-72 Assistant Professor of Statistics, Univ. of California, Berkeley. 1972-77 Associate Professor of Mathematics, University of Arizona. 1977-82 Professor, University of Arizona. 1982-02 Professor, Indiana University (Dept. of Mathematics). 2002- Professor of Mathematics and member of BIO5 faculty, University of Arizona. Visiting Positions 1978-79 Visiting Professor, Indian Statistical Institute. 1979 (Summer) Distinguished Visiting Professor, Math. and Civil Engi- neering, University of Mississippi. 1992 Visiting Professor, University of Bielefeld, Germany, June 26-July 28. 1994 Visiting Professor, University of Bielefeld, Germany, Feb. 15-April 15. 1994 Visiting Professor, University of G¨ottingen, Germany, April 15-June 15. 1996 Visiting Professor, University of Bielefeld, Germany, June 8-July 9. 2000 Visiting Scholar, Stanford University, June-September. 2000-01 Visiting Scholar, Oregon State University. 1 3. Honors and Awards: 1977 Special Invited Paper, Annals of Probability 1978 IMS Fellow 1989 DMV Lecturer (by invitation of the German Mathematical Society) 1994-95 Humboldt Prize (Alexander von Humboldt Forschungspreis) 1996 IMS Special Invited Lecture, IMS Annual Meeting, Chicago (Medal- lion Lecture) 1999 Special Invited Paper, Annals of Applied Probability 2000 Guggenheim Fellowship 4. Professional Associations: Fellow of Institute of Mathematical Statistics American Mathematical Society 5. Research Interests: 1. Markov processes in discrete and continuous time and stochastic differen- tial equations, and their applications to equations of mathematical physics, science, engineering and economics. 2. Analytical theory and refinements of central limit theorems.
    [Show full text]
  • Ronald Christensen
    Ronald Christensen Professor of Statistics University of New Mexico Department of Mathematics and Statistics EDUCATION: Ph.D., Statistics, University of Minnesota, 1983. M.S., Statistics, University of Minnesota, 1976. B.A., Mathematics, University of Minnesota, 1974. EXPERIENCE: 1994- Professor, Department of Mathematics and Statistics, University of New Mexico. 1998-2001, 2003- Founding Director, Statistics Clinic, University of New Mexico. 1988-1994 Associate Professor, Department of Mathematics and Statistics, University of New Mexico. 1982-1988 Assistant Professor, Department of Mathematical Sciences, Montana State Uni- versity. 1994 Visiting Professor, Department of Mathematics and Statistics, University of Canterbury, Chch., N.Z. 1987 Visiting Assistant Professor, Department of Theoretical Statistics, University of Minnesota. RESEARCH INTERESTS: Linear Models Bayesian Inference Log-linear and Logistic Regression Models Statistical Methods SOCIETIES AND HONORS: Fellow of the American Statistical Association, 1996 Fellow of the Institute of Mathematical Statistics, 1998 International Biometric Society American Society for Quality Phi Beta Kappa 1 PUBLICATIONS: 1. Christensen, Ronald (2007). \Notes on the decompostion of effects in full factorial experimental designs." Quality Engineering, accepted. (Letter.) 2. Yang, Mingan, Hanson, Timothy, and Christensen, Ronald (2007). \Nonparametric Bayesian estimation of a bivariate density with interval censored data." Statistics in Medicine, under review. 3. Christensen, Ronald (2007). \Discussion: Dimension reduction, nonparametric regres- sion, and multivariate linear models." Statistical Science, accepted. 4. Christensen, Ronald and Johnson, Wesley (2007). \A Conversation with Seymour Geisser." Statistical Science, accepted. 5. Christensen, Ronald (2006). \Comment on Monahan (2006)." The American Statisti- cian, 60, 295. 6. Christensen, Ronald (2006). \General prediction theory and the role of R2." The American Statistician, under revision.
    [Show full text]
  • IMS Treasurer's Report
    16 . IMS Bulletin Volume 49 . Issue 6 Treasurer’s Report 2019 Introduction Membership Data This report details membership and Table 1 presents the membership data back to 2015. Total individual paid membership in subscription data for the calendar year end the Institute as of December 31, 2019 increased by 15% from December 31, 2018. This 2019. The 2019 fiscal year-end audit report is largely due to an increase in members from mainland China. The total number of paid will be posted online separately in the Fall IMS members in 2019 was 2,788. The IMS had its peak in paid membership in 2008 with of 2020, after the auditors have completed 3,156 members. The IMS Executive Committee continues to look for ways to address our the annual process. membership numbers. In 2019, the total number of IMS mem- TABLE 1: Membership, by Calendar Year bers increased. Subscriptions by institutions 2015 2016 2017 2018 2019 % change decreased this past year by 3% overall, and Regular 1,587 1,565 1,447 1,384 1,397 0.9 % by 4% for IMS core journals. The financial Life/Retired Life 528 541 563 613 617 0.7 % status of the Institute continues to be stable Reduced Country/Retired/IMS China 376 337 370 331 704 100.6 % and strong, and actions are in place to New Graduate 58 113 213 76 70 -7.9 % ensure its long-term stability. Student 1,236 1,094 1,022 828 722 -15.3 % Details of the events of the past year, Total 3,785 3,650 3,615 3,217 3,510 7.1 % and membership, subscription and sales Total excluding free members (students) 2,549 2,556 2,593 2,389 2,788 15.0 % data, are given below.
    [Show full text]