Big and Complex Data Analysis

Chapter 1 Regularization After Marginal Learning for Ultra-High Dimensional Regression Models

Chapter 2 Empirical Likelihood Test for High Dimensional Generalized Linear Models

Chapter 3 Random Projections for Large-Scale Regression

Chapter 4 Testing in the Presence of Nuisance Parameters: Some Comments on Tests Post-Model-Selection and Random Critical Values

Chapter 5 Analysis of Correlated Data with Error-Prone Response Under Generalized Linear Mixed Models

Chapter 6 Bias-Reduced Moment Estimators of Population Spectral Distribution and Their Applications

Chapter 7 Statistical Process Control Charts as a Tool for Analyzing Big Data

Chapter 8 Fast Community Detection in Complex Networks with a K-Depths Classifier

Chapter 9 How Different Are Estimated Genetic Networks of Cancer Subtypes?

Chapter 10 A Computationally Efficient Approach for Modeling Complex and Big Survival Data

Chapter 11 Tests of Concentration for Low-Dimensional and High-Dimensional Directional Data

Chapter 12 Nonparametric Testing for Heterogeneous Correlation

Chapter 13 Optimal Shrinkage Estimation in Heteroscedastic Hierarchical Linear Models

Chapter 14 High Dimensional Data Analysis: Integrating Submodels

Chapter 15 High-Dimensional Classification for Brain Decoding

Chapter 16 Unsupervised Bump Hunting Using Principal Components

Chapter 17 Identifying Gene–Environment Interactions Associated with Prognosis Using Penalized Quantile Regression

Chapter 18 A Mixture of Variance-Gamma Factor Analyzers