| 作者：（瑞士）戴维森（Davisom A C） D V Hinkley |
| preface 1 introduction 2 the basic bootstraps 2.1 introduction 2.2 parametric simulation 2.3 nonparametric simulation 2.4 simple confidence intervals 2.5 reducing error 2.6 statistical issues 2.7 nonparametric approximations for variance and bias 2.8 subsampling methods 2.9 bibliographic notes 2.10 problems 2.11 practicals further ideas 3.1 introduction 3.2 several samples 3.3 semiparametric models 3.4 smooth estimates of f 3.5 censoring 3.6 missing data 3.7 finite population sampling 3.8 hierarchical data 3.9 bootstrapping the bootstrap 3.10 bootstrap diagnostics 3.11 choice of estimator from the data 3.12 bibliographic notes 3.13 problems 3.14 practicals 4 tests 4.1 introduction 4.2 resampling for parametric tests 4.3 nonparametric permutation tests 4.4 nonparametric bootstrap tests 4.5 adjusted p-values 4.6 estimating properties of tests 4.7 bibliographic notes 4.8 problems 4.9 practicals 5 confidence intervals 5.1 introduction 5.2 basic confidence limit methods 5.3 percentile methods 5.4 theoretical comparison of methods 5.5 inversion of significance tests 5.6 double bootstrap methods 5.7 empirical comparison of bootstrap methods 5.8 multiparameter methods 5.9 conditional confidence regions 5.10 prediction 5.11 bibliographic notes 5.12 problems 5.13 practicals 6 linear regression 6.1 introduction 6.2 least squares linear regression 6.3 multiple linear regression 6.4 aggregate prediction error and variable selection 6.5 robust regression 6.6 bibliographic notes 6.7 problems 6.8 practicals 7 farther topics in regression 7.1 introduction 7.2 generalized linear models 7.3 survival data 7.4 other nonlinear models 7.5 misclassification error 7.6 nonparametric regression 7.7 bibliographic notes 7.8 problems 7.9 practicals 8 complex dependence 8.1 introduction 8.2 time series 8.3 point processes 8.4 bibliographic notes 8.5 problems 8.6 practicals 9 improved calculation 9.1 introduction 9.2 balanced bootstraps 9.3 control methods 9.4 importance resampling 9.5 saddlepoint approximation 9.6 bibliographic notes 9.7 problems 9.8 practicals 10 semiparametric likelihood inference 10.1 likelihood 10.2 multinomial-based likelihoods 10.3 bootstrap likelihood 10.4 likelihood based on confidence sets 10.5 bayesian bootstraps 10.6 bibliographic notes 10.7 problems 10.8 practicala 11 computer implementation 11.1 introduction 11.2 basic bootstraps 11.3 further ideas 11.4 tests 11.5 confidence intervals 11.6 linear regression 11.7 further topics in regression 11.8 time series 11.9 improved simulation 11.10 semiparametric likelihoods appendix a. cumulant calculations bibliography name index example index subject index |
内容加载中，请稍后...
商品评论（0条）