Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction

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Bradley Efron (Stanford University, California)

Large-Scale Inference

Empirical Bayes Methods for Estimation, Testing, and Prediction

Bradley Efron (Stanford University, California)

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English

Cambridge University Press
29 November 2012

Mathematics & Sciences; Probability & statistics

Series: Institute of Mathematical Statistics Monographs

We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples.

By: Bradley Efron (Stanford University California)
Imprint: Cambridge University Press
Country of Publication: United Kingdom
Volume: 1
Dimensions: Height: 224mm, Width: 150mm, Spine: 15mm
Weight: 450g
ISBN: 9781107619678
ISBN 10: 110761967X
Series: Institute of Mathematical Statistics Monographs
Pages: 276
Publication Date: 29 November 2012
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Bradley Efron is Max H. Stein Professor of Statistics and Biostatistics at the Stanford University School of Humanities and Sciences, and the Department of Health Research and Policy with the School of Medicine.

Reviews for Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction

'In the last decade, Efron has played a leading role in laying down the foundations of large-scale inference, not only in bringing back and developing old ideas, but also linking them with more recent developments, including the theory of false discovery rates and Bayes methods. We are indebted to him for this timely, readable and highly informative monograph, a book he is uniquely qualified to write. It is a synthesis of many of Efron's own contributions over the last decade with that of closely related material, together with some connecting theory, valuable comments, and challenges for the future. His avowed aim is 'not to have the last word' but to help us deal 'with the burgeoning statistical problems of the 21st century'. He has succeeded admirably.' Terry Speed, International Statistical Review