目录 Preface part i high-dimensional classification chapter 1 high-dimensional classification jianqing fan, yingying fan and yichao wu 1 introduction 2 elements of classifications 3 impact of dimensionality on classification 4 distance-based classification rules 5 feature selection by independence rule 6 loss-based classification 7 feature selection in loss-based classification 8 multi-category classification references chapter 2 fleble large margin classifiers yufeng liu and yichao wu 1 background on classification 2 the support vector machine: the margin formulation and the sv interpretation 3 regularization framework 4 some extensions of the svm: bounded constraint machine and the balancing svm 5 multicategory classifiers 6 probability estimation 7 conclusions and discussions references part ii large-scale multiple testing chapter 3 a compound decision-theoretic approach to large-scale multiple testing t tony cai and wenguang sun 1 introduction 2 fdr controlling procedureased on p-values 3 oracle and adaptive compound decision rules for fdr control 4 simultaneous testing of grouped hypotheses 5 large-scale multiple testing under dependence 6 open problems references part iii model building with variable selection chapter 4 model building with variable selection ming yuan 1 introduction 2 why variable selection 3 classical approaches 4 bayesian and stochastic search 5 regularization 6 towards more interpretable models 7 further readings references chapter 5 bayesian variable selection in regression with networked predictors feng tai, wei pan and aotong shen 1 introduction 2 statistical models 3 estimation 4 results 5 discussion references part iv high-dimensional statistics in genomics chapter 6 high-dimensional statistics in genomics hongzhe li 1 introduction 2 identification of active transcription factors using time-course gene expression data 3 methods for analysis of genomic data with a graphical str 4 statistical methods in eqtl studies 5 discussion and future direction references chapter 7 an overview on joint modeling of censored survival time and longitudinal data runze li and jian-jian ren 1 introduction 2 survival data with longitudinal covariates 3 joint modeling with right censored data 4 joint modeling with interval censored data 5 further studies references part v analysis of survival and longitudinal data chapter 8 survival analysis with high-dimensional covariatein nan 1 introduction 2 regularized cox regression 3 hierarchically penalized cox regression with grouped variables 4 regularized methods for the accelerated failure time model 5 tuning parameter selection and a concluding remark references part vi sufficient dimension reduction in regression chapter 9 sufficient dimension reduction in regression angrong yin 1 introduction 2 sufficient dimension reduction in regression 3 sufficient variable selection (svs) 4 sdr for correlated data and large-p-small-n 5 further discussion references chapter 10 combining statistical procedures lihua chen and yuhong yang 1 introduction 2 combining for adaptation 3 combining procedures for improvement 4 concluding remarks references subject index author index 作者介绍
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