volume 50, pages365–367(2018)Cite this article. ... 2017, with permission from the publisher. https://doi.org/10.1007/s11004-017-9721-y, DOI: https://doi.org/10.1007/s11004-017-9721-y, Over 10 million scientific documents at your fingertips, Not logged in A Review of “Computer Age Statistical Inference” by Bradley Efron and Trevor Hastie Murali Haran 1 Mathematical Geosciences volume 50 , pages 365 – 367 ( 2018 ) Cite this article It may takes up to 1-5 minutes before you received it. Analysis and Recommendations Based on Extensive Comparisons Hastie, Trevor, Tibshirani, Robert, and Tibshirani, Ryan, Statistical Science, 2020 Within group variable selection through the Exclusive Lasso Campbell, Frederick and Allen, Genevera I., Electronic Journal of Statistics, 2017 Highlighting their origins, the book helps us understand each method's roles in inference and/or prediction. And where are we going? This is a preview of subscription content, log in to check access. The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. Mathematical Geosciences 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. You can write a book review and share your experiences. Different applications of this work in medical problems are discussed in refs. Computer Age Statistical Inference Algorithms, Evidence, and Data Science Bradley Efron Trevor Hastie Stanford University. The most comprehensive source for generalized additive models is the text by Hastie and Tibshirani 8, from which the cardioplegia example was taken. If possible, download the file in its original format. Download it once and read it on your Kindle device, PC, phones or tablets. Efron and Hastie demonstrate the ever-growing power of statistical reasoning, past, present, and future." © 2020 Springer Nature Switzerland AG. Math Geosci 50, 365–367 (2018). Tax calculation will be finalised during checkout. × Bradley Efron. viii. Haran, M. A Review of “Computer Age Statistical Inference” by Bradley Efron and Trevor Hastie. Bradley Efron is Max H. Stein Professor, Professor of Statistics, and Professor of Biomedical Data Science at Stanford University. - 188.165.235.61. Analysis and Recommendations Based on Extensive Comparisons Hastie, Trevor, Tibshirani, Robert, and Tibshirani, Ryan, Statistical Science, 2020 Within group variable selection through the Exclusive Lasso Campbell, Frederick and Allen, Genevera I., Electronic Journal of Statistics, 2017 Today I wanted to share another book Hastie wrote, together with Bradley Efron, another colleague of his at Stanford University. It may take up to 1-5 minutes before you receive it. Converted file can differ from the original. Highlighting their origins, the book helps us understand each method's roles in inference and/or prediction. Whether you've loved the book or not, if you give your honest and detailed thoughts then people will find new books that are right for them. The file will be sent to your email address. Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs Book 5) - Kindle edition by Efron, Bradley, Hastie, Trevor. The book ends with speculation on the future direction of statistics and data science. Today I wanted to share another book Hastie wrote, together with Bradley Efron, another colleague of his at Stanford University. Part of Springer Nature. Lasso and Least-Angle Regression (LAR) Interesting connection between Lasso and Forward Stepwise. Carl Morris, Harvard University, Massachusetts^"Computer Age Statistical Inference gives a lucid guide to modern statistical inference for estimation, hypothesis testing, and prediction. Contents Preface xv PubMed Google Scholar. Correspondence to This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Efron and Hastie demonstrate the ever-growing power of statistical reasoning, past, present, and future.’ Carl Morris - Harvard University, Massachusetts 'Computer Age Statistical Inference gives a lucid guide to modern statistical inference for estimation, hypothesis testing, and prediction. Trevor Hastie. Institute of Mathematical Statistics Monographs. It is called Computer Age Statistical Inference (Efron & Hastie, 2016) and is a definite must read for every aspiring data scientist because it illustrates most algorithms commonly used in modern-day statistical inference. Murali Haran. https://doi.org/10.1007/s11004-017-9721-y. Other readers will always be interested in your opinion of the books you've read. brief bio » Book signing at the August 2016 JSM in Chicago. Subscription will auto renew annually. package in R (Efron, Hastie, Johnstone, Tibshirani 2002) Lasso: ^( ) = argmin i 1 N PN i=1(y 0 xTi )2 + jj jj 1 t using lars package in R (Efron, H, Johnstone, Tibshirani 2002) 10/32. The distinctly modern approach integrates methodology and algorithms with statistical inference. Learn more about Institutional subscriptions, Department of Statistics, Pennsylvania State University, University Park, PA, USA, You can also search for this author in To Donna and Lynda. JOURNALOFTHEAMERICANSTATISTICALASSOCIATION 1229 of random forests have been largely left open, even in the standardregressionorclassificationcontexts. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. The file will be sent to your Kindle account. "Efron and Hastie guide us through the maze of breakthrough statistical methodologies following the computing evolution: why they were developed, their properties, and how they are used. 'Efron and Hastie guide us through the maze of breakthrough statistical methodologies following the computing evolution: why they were developed, their properties, and how they are used. How did we get here? Immediate online access to all issues from 2019. Bradley Efron, Trevor Hastie The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. Corrected November 10, 2017. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. May take up to 1-5 minutes before you receive it generalized additive is! “ computer Age statistical inference volume 50, pages365–367 ( 2018 ) Cite this article received.! Phones or tablets Stein Professor, Professor of Statistics and Data Science at Stanford University open... Statistical inference ” by Bradley Efron and Hastie demonstrate the ever-growing power of methodology. - 188.165.235.61 to 1-5 minutes before you received it the introduction of computation. By Bradley Efron is Max H. Stein Professor, Professor of Statistics and! Fingertips, Not logged in - 188.165.235.61 email address discussed in refs the introduction electronic. 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