Chen D.-G., Jin Z., Li G., Li Y., Liu A., Zhao Y. (eds.) New Advances in Statistics and Data Science

New York: Springer, 2017. — 355 p.This book is comprised of the presentations delivered at the 25th ICSA Applied Statistics Symposium held at the Hyatt Regency Atlanta, on June 12-15, 2016. This symposium attracted more than 700 statisticians and data scientists working in academia, government, and industry from all over the world. The theme of this conference was the “Challenge of Big Data and Applications of Statistics,” in recognition of the advent of big data era, and the symposium offered opportunities for learning, receiving inspirations from old research ideas and for developing new ones, and for promoting further research collaborations in the data sciences. The invited contributions addressed rich topics closely related to big data analysis in the data sciences, reflecting recent advances and major challenges in statistics, business statistics, and biostatistics. Subsequently, the six editors selected 19 high-quality presentations and invited the speakers to prepare full chapters for this book, which showcases new methods in statistics and data sciences, emerging theories, and case applications from statistics, data science and interdisciplinary fields. The topics covered in the book are timely and have great impact on data sciences, identifying important directions for future research, promoting advanced statistical methods in big data science, and facilitating future collaborations across disciplines and between theory and practice.Statistical Distances and Their Role in Robustness
The Out-of-Source Error in Multi-Source Cross Validation-Type Procedures
Meta-Analysis for Rare Events As Binary Outcomes
New Challenges and Strategies in Robust Optimal Design for Multicategory Logit Modeling
Testing of Multivariate Spline Growth ModelUncertainty Quantification Using the Nearest Neighbor Gaussian Process
Tuning Parameter Selection in the LASSO with Unspecified Propensity
Adaptive Filtering Increases Power to Detect Differentially Expressed Genes
Estimating Parameters in Complex Systems with Functional Outputs: A Wavelet-Based Approximate Bayesian Computation Approach
A Maximum Likelihood Approach for Non-invasive Cancer Diagnosis Using Methylation Profiling of Cell-Free DNA from BloodA Simple and Efficient Statistical Approach for Designing an Early Phase II Clinical Trial: Ordinal Linear Contrast Test
Landmark-Constrained Statistical Shape Analysis of Elastic Curves and Surfaces
Phylogeny-Based Kernels with Application to Microbiome Association Studies
Accounting for Differential Error in Time-to-Event Analyses Using Imperfect Electronic Health Record-Derived EndpointsModeling Inter-Trade Durations in the Limit Order Market
Assessment of Drug Interactions with Repeated Measurements
Statistical Indices for Risk Tracking in Longitudinal Studies
Statistical Analysis of Labor Market Integration: A Mixture Regression Approach
Bias Correction in Age-Period-Cohort Models Using Eigen Analysis