VERY GOOD: This book is in very good condition. There is a slightly bent front cover corner. There is also a slight flaw in the spine that appears to have been made during construction of the book (see image).
Product Details
From the back cover: "We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines reoutinely produce thousands and sometimes millions of parallel data sets, each with its own estimation of testing problem. Doing thousands of problems at once involves 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."
Chapters
Empirical Bayes and the James-Stein Estimator
Large-Scale Hypothesis Testing
Significance Testing Algorithms
False Discovery Rate Control
Local False Discovery Rates
Theoretical, Permutation, and Empirical Null Distributions
