Computer Age Statistical Inference
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Computer Age Statistical Inference
Algorithms, Evidence, and Data Science
Hastie, Trevor; Efron, Bradley
Cambridge University Press
07/2016
495
Dura
Inglês
9781107149892
15 a 20 dias
Take an exhilarating journey through the modern revolution in statistics with two of the ringleaders.
- 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.
- 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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Take an exhilarating journey through the modern revolution in statistics with two of the ringleaders.
- 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.
- 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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
