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

Available

Description

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.

Product Details

Price
£34.99
Publisher
Cambridge University Press
Publish Date
Language
English
Type
Paperback
EAN/UPC
9781107619678
BIC Categories:

Earn By Promoting Books

Earn money by sharing your favourite books through our Affiliate programme.

Become an Affiliate
We use cookies and similar methods to recognize visitors and remember their preferences. We also use them to help detect unauthorized access or activity that violate our terms of service, as well as to analyze site traffic and performance for our own site improvement efforts. To learn more about these methods, including how to disable them view our Cookie Policy.