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

We live in a new age for statistical inference, where modern scientific technology such as microarrays and f MRI 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.Additional ISBNs0521192498, 110761967X, 0511913001, 1107384478, 9780521192491, 9781107619678, 9780511913006, 9781107384477, 0511911033, 1282818740, 0511916612, 0511917597, 9780511911033, 9781282818743, 9780511916618, 9780511917592Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction 1st Edition is written by Bradley Efron and published by Cambridge University Press. ISBNs for Large-Scale Inference are 9781107384477, 1107384478 and the print ISBNs are 9781107619678, 110761967X. Additional ISBNs include 0521192498, 110761967X, 0511913001, 1107384478, 9780521192491, 9781107619678, 9780511913006, 9781107384477, 0511911033, 1282818740, 0511916612, 0511917597, 9780511911033, 9781282818743, 9780511916618, 9780511917592.