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JSM 2017 in Baltimore the 2017 Joint Statistical Meetings in Baltimore, Maryland, Which Included the CONTENTS IMS Annual Meeting, Took Place from July 29 to August 3
Volume 46 • Issue 6 IMS Bulletin September 2017 JSM 2017 in Baltimore The 2017 Joint Statistical Meetings in Baltimore, Maryland, which included the CONTENTS IMS Annual Meeting, took place from July 29 to August 3. There were over 6,000 1 JSM round-up participants from 52 countries, and more than 600 sessions. Among the IMS program highlights were the three Wald Lectures given by Emmanuel Candès, and the Blackwell 2–3 Members’ News: ASA Fellows; ICM speakers; David Allison; Lecture by Martin Wainwright—Xiao-Li Meng writes about how inspirational these Mike Cohen; David Cox lectures (among others) were, on page 10. There were also five Medallion lectures, from Edoardo Airoldi, Emery Brown, Subhashis Ghoshal, Mark Girolami and Judith 4 COPSS Awards winners and nominations Rousseau. Next year’s IMS lectures 6 JSM photos At the IMS Presidential Address and Awards session (you can read Jon Wellner’s 8 Anirban’s Angle: The State of address in the next issue), the IMS lecturers for 2018 were announced. The Wald the World, in a few lines lecturer will be Luc Devroye, the Le Cam lecturer will be Ruth Williams, the Neyman Peter Bühlmann Yuval Peres 10 Obituary: Joseph Hilbe lecture will be given by , and the Schramm lecture by . The Medallion lecturers are: Jean Bertoin, Anthony Davison, Anna De Masi, Svante Student Puzzle Corner; 11 Janson, Davar Khoshnevisan, Thomas Mikosch, Sonia Petrone, Richard Samworth Loève Prize and Ming Yuan. 12 XL-Files: The IMS Style— Next year’s JSM invited sessions Inspirational, Mathematical If you’re feeling inspired by what you heard at JSM, you can help to create the 2018 and Statistical invited program for the meeting in Vancouver (July 28–August 2, 2018). -
September 2010
THE ISBA BULLETIN Vol. 17 No. 3 September 2010 The official bulletin of the International Society for Bayesian Analysis AMESSAGE FROM THE membership renewal (there will be special provi- PRESIDENT sions for members who hold multi-year member- ships). Peter Muller¨ The Bayesian Nonparametrics Section (IS- ISBA President, 2010 BA/BNP) is already up and running, and plan- [email protected] ning the 2011 BNP workshop. Please see the News from the World section in this Bulletin First some sad news. In August we lost two and our homepage (select “business” and “mee- big Bayesians. Julian Besag passed away on Au- tings”). gust 6, and Arnold Zellner passed away on Au- gust 11. Arnold was one of the founding ISBA ISBA/SBSS Educational Initiative. Jointly presidents and was instrumental to get Bayesian with ASA/SBSS (American Statistical Associa- started. Obituaries on this issue of the Analysis tion, Section on Bayesian Statistical Science) we Bulletin and on our homepage acknowledge Juli- launched a new joint educational initiative. The an and Arnold’s pathbreaking contributions and initiative formalized a long standing history of their impact on the lives of many people in our collaboration of ISBA and ASA/SBSS in related research community. They will be missed dearly! matters. Continued on page 2. ISBA Elections 2010. Please check out the elec- tion statements of the candidates for the upco- In this issue ming ISBA elections. We have an amazing slate ‰ A MESSAGE FROM THE BA EDITOR of candidates. Thanks to the nominating commit- *Page 2 tee, Mike West (chair), Renato Martins Assuncao,˜ Jennifer Hill, Beatrix Jones, Jaeyong Lee, Yasuhi- ‰ 2010 ISBA ELECTION *Page 3 ro Omori and Gareth Robert! ‰ SAVAGE AWARD AND MITCHELL PRIZE 2010 *Page 8 Sections. -
IMS Bulletin 39(4)
Volume 39 • Issue 4 IMS1935–2010 Bulletin May 2010 Meet the 2010 candidates Contents 1 IMS Elections 2–3 Members’ News: new ISI members; Adrian Raftery; It’s time for the 2010 IMS elections, and Richard Smith; we introduce this year’s nominees who are IMS Collections vol 5 standing for IMS President-Elect and for IMS Council. You can read all the candi- 4 IMS Election candidates dates’ statements, starting on page 4. 9 Amendments to This year there are also amendments Constitution and Bylaws to the Constitution and Bylaws to vote Letter to the Editor 11 on: they are listed The candidate for IMS President-Elect is Medallion Preview: Laurens on page 9. 13 Ruth Williams de Haan Voting is open until June 26, so 14 COPSS Fisher lecture: Bruce https://secure.imstat.org/secure/vote2010/vote2010.asp Lindsay please visit to cast your vote! 15 Rick’s Ramblings: March Madness 16 Terence’s Stuff: And ANOVA thing 17 IMS meetings 27 Other meetings 30 Employment Opportunities 31 International Calendar of Statistical Events The ten Council candidates, clockwise from top left, are: 35 Information for Advertisers Krzysztof Burdzy, Francisco Cribari-Neto, Arnoldo Frigessi, Peter Kim, Steve Lalley, Neal Madras, Gennady Samorodnitsky, Ingrid Van Keilegom, Yazhen Wang and Wing H Wong Abstract submission deadline extended to April 30 IMS Bulletin 2 . IMs Bulletin Volume 39 . Issue 4 Volume 39 • Issue 4 May 2010 IMS members’ news ISSN 1544-1881 International Statistical Institute elects new members Contact information Among the 54 new elected ISI members are several IMS members. We congratulate IMS IMS Bulletin Editor: Xuming He Fellow Jon Wellner, and IMS members: Subhabrata Chakraborti, USA; Liliana Forzani, Assistant Editor: Tati Howell Argentina; Ronald D. -
Tea: a High-Level Language and Runtime System for Automating
Tea: A High-level Language and Runtime System for Automating Statistical Analysis Eunice Jun1, Maureen Daum1, Jared Roesch1, Sarah Chasins2, Emery Berger34, Rene Just1, Katharina Reinecke1 1University of Washington, 2University of California, 3University of Seattle, WA Berkeley, CA Massachusetts Amherst, femjun, mdaum, jroesch, [email protected] 4Microsoft Research, rjust, [email protected] Redmond, WA [email protected] ABSTRACT Since the development of modern statistical methods (e.g., Though statistical analyses are centered on research questions Student’s t-test, ANOVA, etc.), statisticians have acknowl- and hypotheses, current statistical analysis tools are not. Users edged the difficulty of identifying which statistical tests people must first translate their hypotheses into specific statistical should use to answer their specific research questions. Almost tests and then perform API calls with functions and parame- a century later, choosing appropriate statistical tests for eval- ters. To do so accurately requires that users have statistical uating a hypothesis remains a challenge. As a consequence, expertise. To lower this barrier to valid, replicable statistical errors in statistical analyses are common [26], especially given analysis, we introduce Tea, a high-level declarative language that data analysis has become a common task for people with and runtime system. In Tea, users express their study de- little to no statistical expertise. sign, any parametric assumptions, and their hypotheses. Tea A wide variety of tools (such as SPSS [55], SAS [54], and compiles these high-level specifications into a constraint satis- JMP [52]), programming languages (e.g., R [53]), and libraries faction problem that determines the set of valid statistical tests (including numpy [40], scipy [23], and statsmodels [45]), en- and then executes them to test the hypothesis. -
December 2000
THE ISBA BULLETIN Vol. 7 No. 4 December 2000 The o±cial bulletin of the International Society for Bayesian Analysis A WORD FROM already lays out all the elements mere statisticians might have THE PRESIDENT of the philosophical position anything to say to them that by Philip Dawid that he was to continue to could possibly be worth ISBA President develop and promote (to a listening to. I recently acted as [email protected] largely uncomprehending an expert witness for the audience) for the rest of his life. defence in a murder appeal, Radical Probabilism He is utterly uncompromising which revolved around a Modern Bayesianism is doing in his rejection of the realist variant of the “Prosecutor’s a wonderful job in an enormous conception that Probability is Fallacy” (the confusion of range of applied activities, somehow “out there in the world”, P (innocencejevidence) with supplying modelling, data and in his pragmatist emphasis P ('evidencejinnocence)). $ analysis and inference on Subjective Probability as Contents procedures to nourish parts that something that can be measured other techniques cannot reach. and regulated by suitable ➤ ISBA Elections and Logo But Bayesianism is far more instruments (betting behaviour, ☛ Page 2 than a bag of tricks for helping or proper scoring rules). other specialists out with their What de Finetti constructed ➤ Interview with Lindley tricky problems – it is a totally was, essentially, a whole new ☛ Page 3 original way of thinking about theory of logic – in the broad ➤ New prizes the world we live in. I was sense of principles for thinking ☛ Page 5 forcibly struck by this when I and learning about how the had to deliver some brief world behaves. -
The BUGS Project: Evolution, Critique and Future Directions
STATISTICS IN MEDICINE Statist. Med. 2009; 28:3049–3067 Published online 24 July 2009 in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/sim.3680 The BUGS project: Evolution, critique and future directions 1, , 1 2 3 David Lunn ∗ †, David Spiegelhalter ,AndrewThomas and Nicky Best 1Medical Research Council Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge CB2 0SR, U.K. 2School of Mathematics and Statistics, Mathematical Institute, North Haugh, St. Andrews, Fife KY16 9SS, U.K. 3Department of Epidemiology and Public Health, Imperial College London, St. Mary’s Campus, Norfolk Place, London W2 1PG, U.K. SUMMARY BUGS is a software package for Bayesian inference using Gibbs sampling. The software has been instru- mental in raising awareness of Bayesian modelling among both academic and commercial communities internationally, and has enjoyed considerable success over its 20-year life span. Despite this, the software has a number of shortcomings and a principal aim of this paper is to provide a balanced critical appraisal, in particular highlighting how various ideas have led to unprecedented flexibility while at the same time producing negative side effects. We also present a historical overview of the BUGS project and some future perspectives. Copyright 2009 John Wiley & Sons, Ltd. KEY WORDS: BUGS; WinBUGS; OpenBUGS; Bayesian modelling; graphical models 1. INTRODUCTION BUGS 1 is a software package for performing Bayesian inference using Gibbs sampling 2, 3 . The BUGS[ ] project began at the Medical Research Council Biostatistics Unit in Cambridge in[ 1989.] Since that time the software has become one of the most popular statistical modelling packages, with, at the time of writing, over 30000 registered users of WinBUGS (the Microsoft Windows incarnation of the software) worldwide, and an active on-line community comprising over 8000 members. -
Design and Analysis Issues in Family-Based Association
Emerging Challenges in Statistical Genetics Duncan Thomas University of Southern California Human Genetics in the Big Science Era • “Big Data” – large n and large p and complexity e.g., NIH Biomedical Big Data Initiative (RFA-HG-14-020) • Large n: challenge for computation and data storage, but not conceptual • Large p: many data mining approaches, few grounded in statistical principles • Sparse penalized regression & hierarchical modeling from Bayesian and frequentist perspectives • Emerging –omics challenges Genetics: from Fisher to GWAS • Population genetics & heritability – Mendel / Fisher / Haldane / Wright • Segregation analysis – Likelihoods on complex pedigrees by peeling: Elston & Stewart • Linkage analysis (PCR / microsats / SNPs) – Multipoint: Lander & Green – MCMC: Thompson • Association – TDT, FBATs, etc: Spielman, Laird – GWAS: Risch & Merikangas – Post-GWAS: pathway mining, next-gen sequencing Association: From hypothesis-driven to agnostic research Candidate pathways Candidate Hierarchical GWAS genes models (ht-SNPs) Ontologies Pathway mining MRC BSU SGX Plans Objectives: – Integrating structural and prior information for sparse regression analysis of high dimensional data – Clustering models for exposure-disease associations – Integrating network information – Penalised regression and Bayesian variable selection – Mechanistic models of cellular processes – Statistical computing for large scale genomics data Targeted areas of impact : – gene regulation and immunological response – biomarker based signatures – targeting -
2016 IAA Awards Outstanding Contributions to Astrostatistics Award
International Astrostatistics Association -------------------------------------------------------------------------------------------------------- Associazione Internazionale di AstroStatistica INAF Osservatorio Astronomico di Brera http://www.brera.mi.astro.it/IAA/ Via Brera, 28, Milano, Italy [email protected] 2016 IAA Awards 20 April, 2016 Outstanding Contributions to Astrostatistics Award Joseph M. Hilbe Joseph Hilbe is the founder and President of the International Astrostatistics Association (IAA), and founded the first astrostatistics interest group and committee under the auspices of an astronomical or statistical organization. Prof. Hilbe is an emeritus professor with the University of Hawaii, an adjunct professor of statistics at Arizona State University, and solar system ambassador with the Jet Propulsion Laboratory. He has authored 18 books in statistical modeling, including very well cited books on count and binomial models from both the frequentist and Bayesian traditions. His book, Modeling Count Data won the Association of American Publishers 2015 PROSE honorable mention award for books on mathematics. He has authored a number of statistical procedures and functions for commercial statistical software as well as in R, many of which have direct applications to astrophysical research. Prof. Hilbe is an elected Fellow of the American Statistical Association, an elected member of the International Statistical Institute, for which he has chaired the committee on astrostatistics from 2009, is a full member of the American Astronomical Society, is editor-in-chief of the Springer Series on Astrostatistics, and founding co-editor of the Astrostatistics & Astroinformatics Portal (ASAIP). 1 Eric D. Feigelson Eric Feigelson is a Distinguish Senior Scholar and Professor in the Department of Astronomy and Astrophysics and the Department of Statistics at Pennsylvania State University. -
Stan User's Guide 2.27
Stan User’s Guide Version 2.27 Stan Development Team Contents Overview 9 Part 1. Example Models 11 1. Regression Models 12 1.1 Linear regression 12 1.2 The QR reparameterization 14 1.3 Priors for coefficients and scales 16 1.4 Robust noise models 16 1.5 Logistic and probit regression 17 1.6 Multi-logit regression 19 1.7 Parameterizing centered vectors 21 1.8 Ordered logistic and probit regression 24 1.9 Hierarchical logistic regression 25 1.10 Hierarchical priors 28 1.11 Item-response theory models 29 1.12 Priors for identifiability 32 1.13 Multivariate priors for hierarchical models 33 1.14 Prediction, forecasting, and backcasting 41 1.15 Multivariate outcomes 42 1.16 Applications of pseudorandom number generation 48 2. Time-Series Models 51 2.1 Autoregressive models 51 2.2 Modeling temporal heteroscedasticity 54 2.3 Moving average models 55 2.4 Autoregressive moving average models 58 2.5 Stochastic volatility models 60 2.6 Hidden Markov models 63 3. Missing Data and Partially Known Parameters 70 1 CONTENTS 2 3.1 Missing data 70 3.2 Partially known parameters 71 3.3 Sliced missing data 72 3.4 Loading matrix for factor analysis 73 3.5 Missing multivariate data 74 4. Truncated or Censored Data 77 4.1 Truncated distributions 77 4.2 Truncated data 77 4.3 Censored data 79 5. Finite Mixtures 82 5.1 Relation to clustering 82 5.2 Latent discrete parameterization 82 5.3 Summing out the responsibility parameter 83 5.4 Vectorizing mixtures 86 5.5 Inferences supported by mixtures 87 5.6 Zero-inflated and hurdle models 90 5.7 Priors and effective data size in mixture models 94 6. -
Cou Tdata Modeling Count Data
MODEL NG COU TDATA MODELING COUNT DATA This definitive entry-level text, authored by a leading statistician in the field, offers clear and concise guidelines on how to select, construct, interpret, and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models, using numerous tables, insets, and detailed modeling suggestions. It begins by demonstrating the fundamentals of modeling count data, including a thor- ough presentation of the Poisson model. It then works up to an analysis of the problem of overdispersion and of the negative binomial model, and finally to the many variations that can be made to the base count models. Examples in Stata, R, and SAS code enable readers to adapt models for their own purposes, making the text an ideal resource for researchers working in health, ecology, econometrics, transportation, and other fields. Joseph M. Hilbe is a solar system ambassador with NASA’s Jet Propulsion Lab- oratory, California Institute of Technology; an adjunct professor of statistics at Arizona State University; an emeritus professor at the University of Hawaii; and an instructor for Statistics.com, a web-based continuing-education pro- gram in statistics. He is currently president of the International Astrostatistics Association, and he is an elected Fellow of the American Statistical Associa- tion, for which he is the current chair of the section on Statistics in Sports. Author of several leading texts on statistical modeling, Hilbe also serves as the coordinating editor for the Cambridge University Press series Predictive Analytics in Action. Other Statistics Books by Joseph M. -
LRP2020: Astrostatistics in Canada Arxiv:1910.08857V1 [Astro-Ph.IM
1 E017: Astrostatistics in Canada LRP2020: Astrostatistics in Canada Authors Gwendolyn Eadie1;2;3;4, Arash Bahramian5, Pauline Barmby6, Radu Craiu2, Derek Bingham7;8, Renee´ Hlozekˇ 1;9, JJ Kavelaars10, David Stenning11, Samantha Benincasa12, Guillaume Thomas10, Karun Thanjavur13, Jo Bovy1;9, Jan Cami6, Ray Carlberg1, Sam Lawler10; Adrian Liu14;15, Henry Ngo10, Mubdi Rahman9, Michael Rupen10 Executive Summary This state-of-the-profession white paper focuses on the interdisciplinary fields of astrostatistics and astroinformat- ics, in which modern statistical and computational methods are applied to and developed for astronomical data. Astrostatistics and astroinformatics have grown dramatically in the past ten years, with international organizations, societies, conferences, workshops, and summer schools becoming the norm. Canada’s formal role in astrostatistics and astroinformatics has been relatively limited, but there is a great opportunity — and necessity — for growth in this area. In the 2020s, extremely large astronomy datasets will be available from both Canadian- and internationally- funded projects and missions. Millions of dollars and thousands of human hours have been invested in order to obtain these data, and we need to make the most of these data when performing scientific inference. Novel statistical and computational methods from astrostatistics and astroinformatics will be the driving force in the next decade of scientific discovery, and interdisciplinary collaboration is key. In order to establish Canada as an international leader in astrostatistics and astroinformatics, we must first understand our current state in these areas. Thus, we conducted a survey of astronomers in Canada to gain informa- tion on the training mechanisms through which we learn statistical methods and to identify areas for improvement. -
Our Place in Space N Ted’S Tour America’S Future N New Deals in Scholarships on the Final Frontier
No 5, 2011 n $5 Our Place in Space n Ted’S TOUR America’s future n NEW DEALS IN SCHOLARSHIPS on the final frontier Contents | September 2011 20 34 26 26 20 34 COVER STORY Money Talks A Beautiful Mind Our Place in Space The University overhauls its Ted Johnson’s campus tours Now that NASA’s space shuttle financial-aid process for new conjure up a whole new way program has cooled its jets, students, introducing renew- of looking at Mount Oread. many KU faculty and alumni able scholarships that make it are left to ponder what’s next easier to help the neediest and By Chris Lazzarino for their research and for attract the best and brightest to America’s exploration of the the Jayhawk fold. final frontier. By Jennifer Sanner Essay by Steven Hawley Story by Terry Rombeck Cover photograph courtesy NASA Established in 1902 as The Graduate Magazine Volume 109, No. 5, 2011 ISSUE 5, 2011 | 1 Lift the Chorus n Lynn H. Nelson taught learned a fair amount of History 108, a medieval history etymology and the medieval Your survey, during fall semester origins of modern English— opinion counts 1975. It was a five-hour class, how, for example, a 13th-cen- Please email us a note meeting each morning in a tury shire reeve became today’s at [email protected] fourth floor classroom in the sheriff. to tell us what you think of southeast corner of Wescoe Professor Nelson was serious your alumni magazine. Hall. and reserved. He was punctual There were about 60 of us.