Front Matter
 Part I High-Dimensional Classication
 Chapter 1 High-Dimensional Classication
  Jianqing Fan, Yingying Fan and Yichao Wu
  1 Introduction
  2 Elements of classications
  3 Impact of dimensionality on classication
  4 Distance-based classication Rules
  5 Feature selection by independence rule
  6 Loss-based classication
  7 Feature selection in loss-based classication
  8 Multi-category classication
  References
 Chapter 2 Flexible Large Margin Classiers
  Yufeng Liu and Yichao Wu
  1 Background on classication
  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 classiers
  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 procedures based 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 Regressionwith Networked Predictors
  Feng Tai, Wei Pan and Xiaotong 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 Identication of active transcription factors using
  time-course gene expression data
  3 Methods for analysis of genomic data with a graphical structure
  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 Covariates
  Bin 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 Sucient Dimension Reduction in Regression
 Chapter 9 Sucient Dimension Reduction in Regression
  Xiangrong Yin
  1 Introduction
  2 Sucient dimension reduction in regression
  3 Sucient 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
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