Big and Complex Data Analysis

Dr. S. Ejaz Ahmed is Dean of the Faculty of Mathematics and Science and a Professor of Statistics at Brock University. Before joining Brock, he was a professor and head of the Mathematics & Statistics Department at the University of Windsor and University of Regina. Prior to that, he was an assistant professor at the University of Western Ontario. He is an elected fellow of the American Statistical Association and holds many adjunct professorship positions. His areas of expertise include big data analysis, statistical inference, and shrinkage estimation. He has more than 150 published articles in scientific journals and has reviewed more than 100 books. Further, he has written several books, edited and co-edited several volumes and special issues of scientific journals. He has supervised numerous PhD and master’s students and organized several workshops/conferences and many invited sessions. Dr. Ahmed serves on the editorial board of many statistical journals and asa review editor for Technometrics. He served as a Board of Director and Chairman of the Education Committee of the Statistical Society of Canada, and as a VP communication for ISBIS. Recently, he served as a member of an Evaluation Group, Discovery Grants and the Grant Selection Committee, Natural Sciences and Engineering Research Council of Canada.

• 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.