000			01622nam a2200181 4500
008			171005b xxu||||| |||| 00| 0 eng d
020			_a9781107149892
082			_a519.50285 _bEFR
100			_aEfron, Bradley _920914
245			_aComputer Age Statistical Inference: Algorithms, Evidence and Data Science
260			_bCambridge University Press _c2017 _aNew York
300			_a475p
500			_aPart 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 Co 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
600			_aBig Data - Statistical Methods _925348
600			_aStatistics - History _925349
700			_aHastie, Trevor _923197
942			_2ddc _cLB _k519.50285 _mEFR
999			_c109428 _d109428