Computer Age Statistical Inference - Algorithms, Evidence, and Data Science

Informationen zum Autor Bradley Efron is Max H. Stein Professor, Professor of Statistics, and Professor of Biomedical Data Science at Stanford University, California. He has held visiting faculty appointments at Harvard University, Massachusetts, the University of California, Berkeley, and Imperial College of Science, Technology and Medicine, London. Efron has worked extensively on theories of statistical inference, and is the inventor of the bootstrap sampling technique. He received the National Medal of Science in 2005 and the Guy Medal in Gold of the Royal Statistical Society in 2014. Klappentext Take an exhilarating journey through the modern revolution in statistics with two of the ringleaders. Zusammenfassung Computing power has revolutionized the theory and practice of statistical inference. This book delivers a concentrated course in modern statistical thinking by tracking the revolution from classical theories to the large-scale prediction algorithms of today. Anyone who applies statistical methods to data will benefit from this landmark text. Inhaltsverzeichnis Part I. Classic Statistical Inference: 1. Algorithms and inference; 2. Frequentist inference; 3. Bayesian inference; 4. Fisherian inference and maximum likelihood estimation; 5. Parametric models and exponential families; Part II. Early Computer-Age Methods: 6. Empirical Bayes; 7. James-Stein estimation and ridge regression; 8. Generalized linear models and regression trees; 9. Survival analysis and the EM algorithm; 10. The jackknife and the bootstrap; 11. Bootstrap confidence intervals; 12. Cross-validation and Cp estimates of prediction error; 13. Objective Bayes inference and Markov chain Monte Carlo; 14. Statistical inference and methodology in the postwar era; Part III. Twenty-First Century Topics: 15. Large-scale hypothesis testing and false discovery rates; 16. Sparse modeling and the lasso; 17. Random forests and boosting; 18. Neural networks and deep learning; 19. Support-vector machines and kernel methods; 20. Inference after model selection; 21. Empirical Bayes estimation strategies; Epilogue; References; Index....

Product details

• Authors: Bradley Efron, Bradley (Stanford University Efron, Bradley Hastie Efron, Trevor Hastie, Trevor (Stanford University Hastie
• Publisher: Cambridge University Press Academic
• Languages: English
• Product format: Hardback
• Released: 31.08.2016
• EAN: 9781107149892
• ISBN: 978-1-107-14989-2
• Dimensions: 158 mm x 235 mm x 27 mm
• Series: Institute of Mathematical Statistics Monographs; Institute of Mathematical Statistics Monographs
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Statistik, Stochastik, Wahrscheinlichkeitsrechnung, Künstliche Intelligenz, Wahrscheinlichkeitsrechnung und Statistik, Epidemiologie und medizinische Statistik, MATHEMATICS / Probability & Statistics / General, Mathematik / Statistik, Englische Bücher / Naturwissenschaften / Mathematik