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Happy 80Th, Ulf!
From SIAM News, Volume 37, Number 7, September 2004 Happy 80th, Ulf! My Grenander Number is two, a distinction that goes all the way back to 1958. In 1951, I wrote a paper on an aspect of the Bergman kernel function with Henry O. Pollak (who later became head of mathematics at the Bell Telephone Laboratories). In 1958, Ulf Grenander, Henry Pollak, and David Slepian wrote on the distribution of quadratic forms in normal varieties. Through my friendship with Henry, I learned of Ulf’s existence, and when Ulf came to Brown in 1966, I felt that this friendship would be passed on to me. And so it turned out. I had already read and appreciated the second of Ulf’s many books: On Toeplitz Forms and Their Applications (1958), written jointly with Gabor Szegö. Over the years, my wife and I have lived a block away from Ulf and “Pi” Grenander. (Pi = π = 3.14159...) We have known their children and their grandchildren. And I shouldn’t forget their many dogs. We have enjoyed their hospitality on numerous occasions, including graduations, weddings, and Lucia Day (December 13). We have visited with them in their summer home in Vastervik, Sweden. We have sailed with them around the nearby islands in the Baltic. And yet, despite the fact that our offices are separated by only a few feet, despite the fact that I have often pumped him for mathematical information and received mathematical wisdom in return, my Grenander Number has never been reduced to one. On May 7, 2004, about fifty people gathered in Warwick, Rhode Island, for an all-day celebration, Ulf Grenander from breakfast through dinner, in honor of Ulf’s 80th birthday. -
Memorial Resolution George Bernard Dantzig (1914–2005)
MEMORIAL RESOLUTION GEORGE BERNARD DANTZIG (1914–2005) George Bernard Dantzig, the C. A. Criley Professor of Transportation Sciences and Professor of Operations Research and of Computer Science, Emeritus, died at his campus home on May 13, 2005 at age 90. Born on November 8, 1914 in Portland, Oregon, George Dantzig was given the middle name “Bernard” as an expression of his parents’ hope that he would become a writer. This was not to be, even though late in his life George was engaged in writing a novel. Instead, George became a mathematician. He graduated from the University of Maryland with an A.B. in mathematics and physics (1936) and took his M.A. in mathematics from the University of Michigan (1938). After a two-year period at the Bureau of Labor Statistics, he enrolled in the doctoral program in mathematics at the University of California, Berkeley, with the intention of writing his dissertation on mathematical statistics under the supervision of Jerzy Neyman. Arriving late to one of Neyman’s lectures, George copied down two problem statements from the blackboard thinking they were a homework assignment. George found these problems challenging. After a while though, he was able to solve them both and turned them in to the professor. As it happened, the problems were not just exercises but open questions in the field. The solutions to these problems became the two independent parts of George’s doctoral dissertation. With the outbreak of World War II, George took a leave of absence from the doctoral program at Berkeley to join the U.S. -
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). -
Strength in Numbers: the Rising of Academic Statistics Departments In
Agresti · Meng Agresti Eds. Alan Agresti · Xiao-Li Meng Editors Strength in Numbers: The Rising of Academic Statistics DepartmentsStatistics in the U.S. Rising of Academic The in Numbers: Strength Statistics Departments in the U.S. Strength in Numbers: The Rising of Academic Statistics Departments in the U.S. Alan Agresti • Xiao-Li Meng Editors Strength in Numbers: The Rising of Academic Statistics Departments in the U.S. 123 Editors Alan Agresti Xiao-Li Meng Department of Statistics Department of Statistics University of Florida Harvard University Gainesville, FL Cambridge, MA USA USA ISBN 978-1-4614-3648-5 ISBN 978-1-4614-3649-2 (eBook) DOI 10.1007/978-1-4614-3649-2 Springer New York Heidelberg Dordrecht London Library of Congress Control Number: 2012942702 Ó Springer Science+Business Media New York 2013 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. -
Zaawansowane Zagadnienia Kombinatoryk
Zał nr 4 do ZW Faculty of Fundamental Problems of Technology COURSE CARD Name in polish : Zaawansowane Zagadnienia Kombinatoryki Name in english : Advanced Topics of Combinatorics Field of study : Computer Science Specialty (if applicable) : Undergraduate degree and form of : masters, stationary Type of course : optional Course code : E2_W30 Group rate : Yes Lectures Exercides Laboratory Project Seminar Number of classes held in schools (ZZU) 30 30 The total number of hours of student wor- 90 90 kload (CNPS) Assesment pass For a group of courses final course mark X Number of ECTS credits 3 3 including the number of points correspon- 3 ding to the classes of practical (P) including the number of points correspon- 3 3 ding occupations requiring direct contact (BK) PREREQUISITES FOR KNOWLEDGE, SKILLS AND OTHER POWERS The knowledge of basic topics of Mathematical analysis 1, Discrete Mathematics and Probabilistic methods and statistics (Probability theory) is required. The elementary knowledge on Graph theory is recommended but not mandatory. COURSE OBJECTIVES C1 Presentation of selected advanced issues of modern combinatorics. C2 Learning modern techniques used to solve combinatorial problems. 1 COURSE LEARNING OUTCOMES The scope of the student’s knowledge: W1 Student understands the concept of issues in extremal combinatorics and is able to indicate their examples. W2 Student knows the basics of Ramsey theory. W3 Student knows the elementary issues of percolation and understands their threshold nature. The student skills: U1 Student can apply basic probability tools in analyzing a combinatorial problem U2 Student can use the theorems of Ramsey theory to identify features of mathematical objects. U3 Student can indicate threshold character of different percolation processes. -
A Pattern Theoretic Approach
The Modelling of Biological Growth: a Pattern Theoretic Approach Nataliya Portman, Postdoctoral fellow McConnell Brain Imaging Centre Montreal Neurological Institute McGill University June 21, 2011 The Modelling of Biological Growth: a Pattern Theoretic Approach 2/ 47 Dedication This research work is dedicated to my PhD co-supervisor Dr. Ulf Grenander, the founder of Pattern Theory Division of Applied Mathematics, Brown University Providence, Rhode Island, USA. http://www.dam.brown.edu/ptg/ The Modelling of Biological Growth: a Pattern Theoretic Approach 3/ 47 Outline 1 Mathematical foundations of computational anatomy 2 Growth models in computational anatomy 3 A link between anatomical models and the GRID model 4 GRID view of growth on a fine time scale 5 GRID equation of growth on a coarse time scale (macroscopic growth law) 6 Image inference of growth properties of the Drosophila wing disc 7 Summary, concluding remarks and future perspectives 8 Current work The Modelling of Biological Growth: a Pattern Theoretic Approach 4/ 47 Mathematical foundations of computational anatomy Mathematical foundations of computational anatomy Computational anatomy1 focuses on the precise study of the biological variability of brain anatomy. D'Arcy Thompson laid out the vision of this discipline in his treatise \On Growth and Form" 2. In 1917 he wrote \In a very large part of morphology, our essential task lies in the comparison of related forms rather than in the precise definition of each; and the deformation of a complicated figure may be a phenomenon easy of comprehension, though the figure itself may be left unanalyzed and undefined." D'Arcy Thompson introduced the Method of Coordinates to accomplish the process of comparison. -
Proceedings of the Fourth Berkeley Symposium
PROCEEDINGS OF THE FOURTH BERKELEY SYMPOSIUM VOLUME III PROCEEDINGS of the FOURTH BERKELEY SYMPOSIUM ON MATHEMATICAL STATISTICS AND PROBABILITY Held at the Statistical Laboratory University of California June 20-jtuly 30, 1960, with the support of University of California National Science Foundation Office of Naval Research Office of Ordnance Research Air Force Office of Research National Institutes of Health VOLUME III CONTRIBUTIONS TO ASTRONOMY, METEOROLOGY, AND PHYSICS EDITED BY JERZY NEYMAN UNIVERSITY OF CALIFORNIA PRESS BERKELEY AND LOS ANGELES 1961 UNIVERSITY OF CALIFORNIA PRESS BERKELEY AND LOS ANGELES CALIFORNIA CAMBRIDGE UNIVERSITY PRESS LONDON, ENGLAND © 1961, BY THE REGENTS OF THE UNIVERSITY OF CALIFORNIA The United States Government and its offices, agents, an I em- ployees, acting within the scope of their duties, may reproduce, publish, and use this material in whole or in part for governmental purposes without payment of royalties thereon or therefor. The publication or republication by the government either separately or in a public document of any material in which copyright subsists shall not be taken to cause any abridgment or annulment of the copyright or to authorize any use or appropriation of such copy- right material without the consent of the copyright proprietor. LIBRARY OF CONGRESS CATALOG CARD NUMBER: 49-8189 PRINTED IN THE UNITED STATES OF AMERICA CONTENTS OF PROCEEDINGS, VOLUMES I, II, AND IV Volume I-Theory of Statistics F. J. ANSCOMBE, Examination of residuals. RICHARD BELLMAN, A mathematical formulation of variational processes of adaptive type. Z. W. BIRNBAUM, On the probabil- istic theory of complex structuires. DAVID BLACKWELL, Exponential error bounds for finite state channels. -
Academic Genealogy of the Oakland University Department Of
Basilios Bessarion Mystras 1436 Guarino da Verona Johannes Argyropoulos 1408 Università di Padova 1444 Academic Genealogy of the Oakland University Vittorino da Feltre Marsilio Ficino Cristoforo Landino Università di Padova 1416 Università di Firenze 1462 Theodoros Gazes Ognibene (Omnibonus Leonicenus) Bonisoli da Lonigo Angelo Poliziano Florens Florentius Radwyn Radewyns Geert Gerardus Magnus Groote Università di Mantova 1433 Università di Mantova Università di Firenze 1477 Constantinople 1433 DepartmentThe Mathematics Genealogy Project of is a serviceMathematics of North Dakota State University and and the American Statistics Mathematical Society. Demetrios Chalcocondyles http://www.mathgenealogy.org/ Heinrich von Langenstein Gaetano da Thiene Sigismondo Polcastro Leo Outers Moses Perez Scipione Fortiguerra Rudolf Agricola Thomas von Kempen à Kempis Jacob ben Jehiel Loans Accademia Romana 1452 Université de Paris 1363, 1375 Université Catholique de Louvain 1485 Università di Firenze 1493 Università degli Studi di Ferrara 1478 Mystras 1452 Jan Standonck Johann (Johannes Kapnion) Reuchlin Johannes von Gmunden Nicoletto Vernia Pietro Roccabonella Pelope Maarten (Martinus Dorpius) van Dorp Jean Tagault François Dubois Janus Lascaris Girolamo (Hieronymus Aleander) Aleandro Matthaeus Adrianus Alexander Hegius Johannes Stöffler Collège Sainte-Barbe 1474 Universität Basel 1477 Universität Wien 1406 Università di Padova Università di Padova Université Catholique de Louvain 1504, 1515 Université de Paris 1516 Università di Padova 1472 Università -
2018 Ulf Grenander Prize in Stochastic Theory and Modeling
AMS Prize Announcements FROM THE AMS SECRETARY 2018 Ulf Grenander Prize in Stochastic Theory and Modeling Judea Pearl was awarded the inaugural Ulf Grenander Prize in Stochastic Theory and Modeling at the 124th Annual Meeting of the AMS in San Diego, California, in January 2018. Citation belief propagation algorithm in Bayesian networks, which The 2018 Grenander Prize in recast the problem of computing posterior distributions Stochastic Theory and Modeling given evidence as a scheme for passing local messages is awarded to Judea Pearl for between network variables. Although exact computations the invention of a model-based through dynamic programming are possible, Pearl recog- approach to probabilistic and nized that in most problems of interest this would not be causal reasoning, for the discov- feasible, and in fact belief propagation turned out to be ery of innovative tools for infer- remarkably effective in many applications. ring these models from observa- Pearl’s primary goal in adopting Bayesian networks for tions, and for the development formulating structured models of complex systems was of novel computational methods his conviction that Bayesian networks would prove to be Judea Pearl for the practical applications of the right platform for addressing one of the most funda- these models. mental challenges to statistical modeling: the identifica- Grenander sought to develop general tools for con- tion of the conditional independencies among correlated structing realistic models of patterns in natural and variables that are induced by truly causal relationships. man-made systems. He believed in the power of rigorous In a series of papers in the 1990s, Pearl clearly showed mathematics and abstraction for the analysis of complex that statistical and causal notions are distinct and how models, statistical theory for efficient model inference, graphical causal models can provide a formal link between and the importance of computation for bridging theory causal quantities of interest and observed data. -
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. -
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. -
BCASA Newsletter Page 1 of 29
BostonBCASA Chapter of theNEWSLETTER American Statistical Association Serving Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont Volume 35, No. 3, January 2017 Homepage: http://www.amstat.org/chapters/boston E-Mail: [email protected] SCHEDULED EVENTS & MEETINGS January 28, 2017, BCASA Annual Winter Potluck Dinner and Party Carlisle, MA Statistical Practice: Innovations and Best Practices for the Applied February 23-25, 2017 Jacksonville, FL Statisticians March 8, 2017 Annual Mosteller Statistician of the Year Award Banquet Simmons College April 8, 2017 Short Course: Introduction to Statistics for Spatio-Temporal Data Cambridge, MA April 21-22, 2017 The New England Statistics Symposium (NESS) Storrs, CT May 5, 2017 Adaptive Designs in Clinical Trials Cambridge, MA May 22-25, 2017 Modern Modeling Methods (M3) Conference Storrs, CT May 2017 Annual Meeting and Spring Social TBD July 29 – August 3, 2017 Joint Statistical Meetings Baltimore, MD September 23, 2017 2017 New England Symposium on Statistics in Sports Cambridge, MA Event schedule at the chapter website: http://www.amstat.org/chapters/boston Detailed announcements appear later in this newsletter. All events are announced in advance to members on our email list. We are currently planning events for the coming year. If you have suggestions please contact Program Chair Fotios Kokkotos, [email protected] _________________________________________________________________________________________________________________________________________ BCASA Newsletter Page 1 of 29 A NOTE FROM THE PLANNING COMMITTEE Welcome back. And Happy New Year to All! This edition of the newsletter begins with Presidents’ Reports from outgoing president James McDougall and incoming president Greta Ljung. We thank Jim for his excellent service as president during the past two years and we welcome Greta as our new president.