Dekorationsartikel gehören nicht zum Leistungsumfang.
Sprache:
Englisch
117,70 €*
Versandkostenfrei per Post / DHL
Aktuell nicht verfügbar
Kategorien:
Beschreibung
Take an exhilarating journey through the modern revolution in statistics with two of the ringleaders.
Take an exhilarating journey through the modern revolution in statistics with two of the ringleaders.
Über den 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.
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.
Details
Erscheinungsjahr: | 2019 |
---|---|
Fachbereich: | Wahrscheinlichkeitstheorie |
Genre: | Importe, Mathematik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
ISBN-13: | 9781107149892 |
ISBN-10: | 1107149894 |
Sprache: | Englisch |
Ausstattung / Beilage: | HC gerader Rücken kaschiert |
Einband: | Gebunden |
Autor: |
Efron, Bradley
Hastie, Trevor |
Hersteller: | Cambridge University Press |
Maße: | 235 x 157 x 31 mm |
Von/Mit: | Bradley Efron (u. a.) |
Erscheinungsdatum: | 15.02.2019 |
Gewicht: | 0,864 kg |
Über den 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.
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.
Details
Erscheinungsjahr: | 2019 |
---|---|
Fachbereich: | Wahrscheinlichkeitstheorie |
Genre: | Importe, Mathematik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
ISBN-13: | 9781107149892 |
ISBN-10: | 1107149894 |
Sprache: | Englisch |
Ausstattung / Beilage: | HC gerader Rücken kaschiert |
Einband: | Gebunden |
Autor: |
Efron, Bradley
Hastie, Trevor |
Hersteller: | Cambridge University Press |
Maße: | 235 x 157 x 31 mm |
Von/Mit: | Bradley Efron (u. a.) |
Erscheinungsdatum: | 15.02.2019 |
Gewicht: | 0,864 kg |
Warnhinweis