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自助法及其应用 版权信息
- ISBN：9787510005510
- 条形码：9787510005510 ; 978-7-5100-0551-0
- 装帧：一般胶版纸
- 册数：暂无
- 重量：暂无
- 所属分类：>
自助法及其应用 内容简介
this series of high quality upper-division textbooks and expository monographs covers all areas of stochastic applicable mathematics. the topics range from pure and applied statistics to probability theory，operations research, mathematical programming, and optimzation. the books contain clear presentations of new developments in the field and also of the state of the art in classical methods. while emphasizing rigorous treatment of theoretical methods, the books contain important applications and discussionsof new techniques made possible be advances in computational methods.
自助法及其应用 目录
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
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
展开全部
自助法及其应用 节选
《自助法及其应用》内容简介： Wedecidedtotrytowriteabalanced account ofresamplingmethods,toincludebasic aspects of the theory which underpinned the methods，and to show as manyapplications as we could in order to illustrate the fun potential of the methods-warts and alL We quickly realized that in order for uS and others to understandand use the bootstrap，we would need suitable software，and producing it led usfurther towards a practically oriented treatment.0ur view was cemented by twofurther developments：the appearance oftwo excellent books，one bv PIeter Hallon the asymptotic theory and the other on basic methods bv Bradley Efron andRobert Tibshirani；and the chance to give further courses that included practicals.Our experience has been that hands-on computing is essential in coming to gripswith resampling ideas,so we have included practicals in this booL as well as moretheoretical problems.
自助法及其应用 作者简介
作者：（瑞士）戴维森（Davisom A C） D V Hinkley
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