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Past, Present, and Future of Statistical Science

Past, Present, and Future of Statistical Science

Abstract

The History of COPSS A brief history of the Committee of Presidents of Statistical Societies (COPSS) Ingram Olkin Reminiscences and Personal Reflections on Career Paths Reminiscences of the Columbia University Department of Mathematical Statistics in the late 1940s Ingram Olkin A career in statistics Herman Chernoff ". . . how wonderful the field of statistics is . . ." David R. Brillinger An unorthodox journey to statistics: Equity issues, remarks on multiplicity Juliet Popper Shaffer Statistics before and after my COPSS Prize Peter J. Bickel The accidental biostatistics professor Donna Brogan Developing a passion for statistics Bruce G. Lindsay Reflections on a statistical career and their implications R. Dennis Cook Science mixes it up with statistics Kathryn Roeder Lessons from a twisted career path Jeffrey S. Rosenthal Promoting equity Mary Gray Perspectives on the Field and Profession Statistics in service to the nation Stephen E. Fienberg Where are the majors? Iain M. Johnstone We live in exciting times Peter Hall The bright future of applied statistics Rafael A. Irizarry The road travelled: From a statistician to a statistical scientist Nilanjan Chatterjee Reflections on a journey into statistical genetics and genomics Xihong Lin Reflections on women in statistics in Canada Mary E. Thompson "The whole women thing" Nancy Reid Reflections on diversity Louise Ryan Reflections on the Discipline Why does statistics have two theories? Donald A.S. Fraser Conditioning is the issue James O. Berger Statistical inference from a Dempster-Shafer perspective Arthur P. Dempster Nonparametric Bayes David B. Dunson How do we choose our default methods? Andrew Gelman Serial correlation and Durbin-Watson bounds T.W. Anderson A non-asymptotic walk in probability and statistics Pascal Massart The past's future is now: What will the present's future bring? Lynne Billard Lessons in biostatistics Norman E. Breslow A vignette of discovery Nancy Flournoy Statistics and public health research Ross L. Prentice Statistics in a new era for finance and health care Tze Leung Lai Meta-analyses: Heterogeneity can be a good thing Nan M. Laird Good health: Statistical challenges in personalizing disease prevention Alice S. Whittemore Buried treasures Michael A. Newton Survey sampling: Past controversies, current orthodoxy, future paradigms Roderick J.A. Little Environmental informatics: Uncertainty quantification in the environmental sciences Noel A. Cressie A journey with statistical genetics Elizabeth Thompson Targeted learning: From MLE to TMLE Mark van der Laan Statistical model building, machine learning, and the ah-ha moment Grace Wahba In praise of sparsity and convexity Robert J. Tibshirani Features of Big Data and sparsest solution in high confidence set Jianqing Fan Rise of the machines Larry A. Wasserman A trio of inference problems that could win you a Nobel Prize in statistics (if you help fund it) Xiao-Li Meng Advice for the Next Generation Inspiration, aspiration, ambition C.F. Jeff Wu Personal reflections on the COPSS Presidents' Award Raymond J. Carroll Publishing without perishing and other career advice Marie Davidian Converting rejections into positive stimuli Donald B. Rubin The importance of mentors Donald B. Rubin Never ask for or give advice, make mistakes, accept mediocrity, enthuse Terry Speed Thirteen rules Bradley Efron

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Average
Average
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