Modern Multidimensional Scaling Modern Multidimensional Scaling
Springer Series in Statistics

Modern Multidimensional Scaling

Theory and Applications

    • US$149.99
    • US$149.99

출판사 설명

The book provides a comprehensive treatment of multidimensional scaling (MDS), a family of statistical techniques for analyzing the structure of (dis)similarity data. Such data are widespread, including, for example, intercorrelations of survey items, direct ratings on the similarity on choice objects, or trade indices for a set of countries. MDS represents the data as distances among points in a geometric space of low dimensionality. This map can help to see patterns in the data that are not obvious from the data matrices. MDS is also used as a psychological model for judgments of similarity and preference.


This book may be used as an introduction to MDS for students in psychology, sociology, and marketing. The prerequisite is an elementary background in statistics. The book is also well suited for a variety of advanced courses on MDS topics. All the mathematics required for more advanced topics is developed systematically.


This second edition is not only a complete overhaul of its predecessor, but also adds some 140 pages of new material. Many chapters are revised or have sections reflecting new insights and developments in MDS. There are two new chapters, one on asymmetric models and the other on unfolding. There are also numerous exercises that help the reader to practice what he or she has learned, and to delve deeper into the models and its intricacies. These exercises make it easier to use this edition in a course. All data sets used in the book can be downloaded from the web. The appendix on computer programs has also been updated and enlarged to reflect the state of the art.


Ingwer Borg is Scientific Director at the Center for Survey Methodology (ZUMA) in Mannheim, Germany, and Professor of Psychology at the University of Giessen, Germany. He has authored or edited 14 books and numerous articles on data analysis, survey research, theory construction, and various substantive topics of psychology. He also served as president of several professional organizations.


Patrick Groenen is Professor in Statistics at the Econometric Institute of the Erasmus University Rotterdam, the Netherlands. Before, he was assistant professor at the Department of Data Theory at Leiden University in the Netherlands. He is an associate editor for three international journals. He has published on MDS, unfolding, optimization, multivariate analysis, and data analysis in various top journals.

장르
논픽션
출시일
2007년
4월 27일
언어
EN
영어
길이
636
페이지
출판사
Springer New York
판매자
Springer Nature B.V.
크기
13.2
MB
The Elements of Statistical Learning The Elements of Statistical Learning
2009년
Regression Modeling Strategies Regression Modeling Strategies
2015년
Forecasting with Exponential Smoothing Forecasting with Exponential Smoothing
2008년
An Introduction to Sequential Monte Carlo An Introduction to Sequential Monte Carlo
2020년
Simulation and Inference for Stochastic Differential Equations Simulation and Inference for Stochastic Differential Equations
2009년
Permutation, Parametric, and Bootstrap Tests of Hypotheses Permutation, Parametric, and Bootstrap Tests of Hypotheses
2006년