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Software Reliability Modeling
Software reliability is one of the most important characteristics of software product quality. Its measurement and management technologies during the software product life cycle …
Modern Methodology and Applications in Spatial-Temporal Modeling
? This book provides a modern introductory tutorial on specialized methodological and applied aspects of spatial and temporal modeling. The areas covered involve a range of topics …
Applied Matrix and Tensor Variate Data Analysis
This book provides comprehensive reviews of recent progress in matrix variate and tensor variate data analysis from applied points of view. Matrix and tensor approaches for data …
Dose-Finding Designs for Early-Phase Cancer Clinical Trials
This book provides a comprehensive introduction to statistical methods for designing early phase dose-finding clinical trials. It will serve as a textbook or handbook for graduate …
Conditional Independence and Linear Programming
This book is the first to be devoted to the fusion between statistical causal inference and mathematical programming. The main purpose of the book is to provide the algorithms for …
Group-Sequential Clinical Trials with Multiple Co-Objectives
This book focuses on group sequential methods for clinical trials with co-primary endpoints based on the decision-making frameworks for: (1) rejecting the null hypothesis (stopping …
Algebraic and Computational Aspects of Real Tensor Ranks
This book provides comprehensive summaries of theoretical (algebraic) and computational aspects of tensor ranks, maximal ranks, and typical ranks, over the real number field. …
Theoretical Aspects of Spatial-Temporal Modeling
This book provides a modern introductory tutorial on specialized theoretical aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the …
Consistency of an Information Criterion for High-Dimensional Multivariate Regression
This is the first book on an evaluation of (weak) consistency of an information criterion for variable selection in high-dimensional multivariate linear regression models by using …