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Written by well-known, award-winning authors, this is the first book to focus on high-dimensional data analysis while presenting real-world applications and research material. Emphasizing that high-dimensional asymptotic distribution can be used for a large range of samples and dimensions to achieve high levels of accuracy, this timely text provides approximation formulas, actual applications, thorough analysis of the real data, and solutions to each problem that are useful to both practical and...

The development and application of multivariate statistical techniques in process monitoring has gained substantial interest over the past two decades in academia and industry alike. Initially developed for monitoring and fault diagnosis in complex systems, such techniques have been refined and applied in various engineering areas, for example mechanical and manufacturing, chemical, electrical and electronic, and power engineering. The recipe for the tremendous interest in multivariate statist...

Categorical data-comprising counts of individuals, objects, or entities in different categories-emerge frequently from many areas of study, including medicine, sociology, geology, and education. They provide important statistical information that can lead to real-life conclusions and the discovery of fresh knowledge. Therefore, the ability to manipulate, understand, and interpret categorical data becomes of interest-if not essential-to professionals and students in a broad range of disciplines....

Featuring a practical approach with numerous examples, this book focuses on helping the reader develop a conceptual, rather than technical, understanding of categorical methods, making it a much more accessible text than others on the market. The authors cover common categorical analyses and emphasize specific research questions that can be addressed by each analytic procedure so that readers are able to address the research questions they wish to answer. To achieve this goal, the authors: Revi...

This systematic and comprehensive account of asymptotic sets and functions develops a broad and useful theory in the areas of optimization and variational inequalities. The central focus is on problems of handling unbounded situations, using solutions of a given problem in these classes, when for example standard compacity hypothesis is not present. This book will interest advanced graduate students, researchers, and practitioners of optimization theory, nonlinear programming, and applied mathem...

A comprehensive, data-driven introduction to modern spatial data analysis, a field which is playing an increasing role in many areas of research and policy making. Provides full explanations for a wide variety of methods, with illustrated with case studies. Data sets for all the case studies are included on an accompanying computer disk, together with a substantial interactive DOS software package for the display and analysis of spatial data.

This authoritative treatment of continuous multivariate distributions (CMD) focuses on the many ways in which various statistical distributions have been constructed, investigated, and applied over the past thirty-plus years. With more than 300 updated references and additional software algorithms, this comprehensive Third Edition of what is widely recognized as the definitive work on statistical distributions, includes a unique collection that encompasses continuous multivariate distributions,...

The most accessible introduction to the theory and practice of multivariate analysis Multivariate Statistical Inference and Applications is a user-friendly introduction to basic multivariate analysis theory and practice for statistics majors as well as nonmajors with little or no background in theoretical statistics. Among the many special features of this extremely accessible first text on multivariate analysis are: Clear, step-by-step explanations of all key concepts and procedures along wit...

With recent advances in computing power and the widespread availability of preference, perception and choice data, such as public opinion surveys and legislative voting, the empirical estimation of spatial models using scaling and ideal point estimation methods has never been more accessible.The second edition of Analyzing Spatial Models of Choice and Judgment demonstrates how to estimate and interpret spatial models with a variety of methods using the open-source programming language R. Requir...

Although nearly all major social science departments offer graduate students training in quantitative methods, the typical sequencing of topics generally delays training in regression analysis and other multivariate techniques until a student's second year. William Berry and Mitchell Sanders's Understanding Multivariate Research fills this gap with a concise introduction to regression analysis and other multivariate techniques. Their book is designed to give new graduate students a grasp of mult...

Applied Univariate, Bivariate, and Multivariate Statistics Using Python A practical, "how-to" reference for anyone performing essential statistical analyses and data management tasks in Python Applied Univariate, Bivariate, and Multivariate Statistics Using Python delivers a comprehensive introduction to a wide range of statistical methods performed using Python in a single, one-stop reference. The book contains user-friendly guidance and instructions on using Python to run a variety of statist...