Bradley Efron explains how to perform thousands of simultaneous estimates and tests, as required by new scientific technology.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.
Inhaltsangabe
Introduction and foreword 1. Empirical Bayes and the James-Stein estimator 2. Large-scale hypothesis testing 3. Significance testing algorithms 4. False discovery rate control 5. Local false discovery rates 6. Theoretical, permutation and empirical null distributions 7. Estimation accuracy 8. Correlation questions 9. Sets of cases (enrichment) 10. Combination, relevance, and comparability 11. Prediction and effect size estimation A. Exponential families B. Programs and data sets Bibliography Index.
