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Computer Age Statistical Inference, Student Edition
Algorithms, Evidence, and Data Science
Taschenbuch von Bradley Efron (u. a.)
Sprache: Englisch

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Beschreibung
Now in paperback and fortified with exercises, this brilliant, enjoyable text demystifies data science, statistics and machine learning.
Now in paperback and fortified with exercises, this brilliant, enjoyable text demystifies data science, statistics and machine learning.
Über den Autor
Bradley Efron is Max H. Stein Professor, Professor of Statistics, and Professor of Biomedical Data Science at Stanford University. He has held visiting faculty appointments at Harvard, UC Berkeley, and Imperial College 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, the Guy Medal in Gold of the Royal Statistical Society in 2014, and the International Prize in Statistics in 2019.
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; Author Index; Subject Index.
Details
Erscheinungsjahr: 2021
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 491
Reihe: Institute of Mathematical Statistics Monographs
Inhalt: Kartoniert / Broschiert
ISBN-13: 9781108823418
ISBN-10: 1108823416
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Efron, Bradley
Hastie, Trevor
Hersteller: Cambridge University Pr.
Abbildungen: Worked examples or Exercises
Maße: 227 x 151 x 23 mm
Von/Mit: Bradley Efron (u. a.)
Erscheinungsdatum: 30.06.2021
Gewicht: 0,812 kg
preigu-id: 119698209
Über den Autor
Bradley Efron is Max H. Stein Professor, Professor of Statistics, and Professor of Biomedical Data Science at Stanford University. He has held visiting faculty appointments at Harvard, UC Berkeley, and Imperial College 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, the Guy Medal in Gold of the Royal Statistical Society in 2014, and the International Prize in Statistics in 2019.
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; Author Index; Subject Index.
Details
Erscheinungsjahr: 2021
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 491
Reihe: Institute of Mathematical Statistics Monographs
Inhalt: Kartoniert / Broschiert
ISBN-13: 9781108823418
ISBN-10: 1108823416
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Efron, Bradley
Hastie, Trevor
Hersteller: Cambridge University Pr.
Abbildungen: Worked examples or Exercises
Maße: 227 x 151 x 23 mm
Von/Mit: Bradley Efron (u. a.)
Erscheinungsdatum: 30.06.2021
Gewicht: 0,812 kg
preigu-id: 119698209
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