Big and Complex Data Analysis [electronic resource] Methodologies and Applications / edited by S. Ejaz Ahmed.

This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Its peer-reviewed contributions showcase recent advances in variable selection, estimation and prediction strategies for a host of useful models, as well as essent...

Full description

Bibliographic Details
Uniform Title:Contributions to Statistics
Corporate Author: SpringerLink (Online service)
Other Authors: Ahmed, S. Ejaz (Editor)
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2017.
Edition:1st ed. 2017.
Series:Contributions to Statistics
Subjects:
Statistics .
Mathematical statistics—Data processing.
Quantitative research.
Biometry.
Data mining.
Online Access:
Springer Mathematics and Statistics eBooks 2017 English/International: 2017 (Springer Link)
Variant Title:
Big and Complex Data Analysis: Methodologies and Applications
Format: Electronic eBook
Contents:
  • Preface
  • Introduction
  • Unsupervised Bump Hunting Using Principal Components
  • Statistical Process Control Charts as a Tool for Analyzing Big Data
  • Empirical Likelihood Test for High Dimensional Generalized Linear Models
  • Identifying gene-environment interactions associated with prognosis using penalized quantile regression
  • A Computationally Efficient Approach for Modeling Complex and Big Survival Data
  • Regularization after marginal learning for ultra-high dimensional regression models
  • Tests of concentration for low-dimensional and high-dimensional directional data
  • Random Projections For Large-Scale Regression
  • How Different are Estimated Genetic Networks of Cancer Subtypes?
  • Analysis of correlated data with error-prone response under generalized linear mixed models
  • High-Dimensional Classification for Brain Decoding
  • Optimal shrinkage estimation in heteroscedastic hierarchical linear models
  • Bias-reduced moment estimators of Population Spectral Distribution and their applications
  • Testing in the Presence of Nuisance Parameters: Some Comments on Tests Post-Model-Selection and Random Critical Values
  • A Mixture of Variance-Gamma Factor Analyzers
  • Fast Community Detection in Complex Networks with a K-Depths Classifier.