Multidimensional Similarity Structure Analysis
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Author | : I. Borg |
Publisher | : Springer Science & Business Media |
Total Pages | : 402 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 1461247683 |
Multidimensional Similarity Structure Analysis comprises a class of models that represent similarity among entities (for example, variables, items, objects, persons, etc.) in multidimensional space to permit one to grasp more easily the interrelations and patterns present in the data. The book is oriented to both researchers who have little or no previous exposure to data scaling and have no more than a high school background in mathematics and to investigators who would like to extend their analyses in the direction of hypothesis and theory testing or to more intimately understand these analytic procedures. The book is repleted with examples and illustrations of the various techniques drawn largely, but not restrictively, from the social sciences, with a heavy emphasis on the concrete, geometric or spatial aspect of the data representations.
Author | : Ingwer Borg |
Publisher | : Springer Science & Business Media |
Total Pages | : 469 |
Release | : 2013-04-18 |
Genre | : Mathematics |
ISBN | : 1475727119 |
Multidimensional scaling (MDS) is a technique for the analysis of similarity or dissimilarity data on a set of objects. Such data may be intercorrelations of test items, ratings of similarity on political candidates, or trade indices for a set of countries. MDS attempts to model such data as distances among points in a geometric space. The main reason for doing this is that one wants a graphical display of the structure of the data, one that is much easier to understand than an array of numbers and, moreover, one that displays the essential information in the data, smoothing out noise. There are numerous varieties of MDS. Some facets for distinguishing among them are the particular type of geometry into which one wants to map the data, the mapping function, the algorithms used to find an optimal data representation, the treatment of statistical error in the models, or the possibility to represent not just one but several similarity matrices at the same time. Other facets relate to the different purposes for which MDS has been used, to various ways of looking at or "interpreting" an MDS representation, or to differences in the data required for the particular models. In this book, we give a fairly comprehensive presentation of MDS. For the reader with applied interests only, the first six chapters of Part I should be sufficient. They explain the basic notions of ordinary MDS, with an emphasis on how MDS can be helpful in answering substantive questions.
Author | : I. Borg |
Publisher | : |
Total Pages | : 408 |
Release | : 1987-07-01 |
Genre | : |
ISBN | : 9781461247692 |
Author | : Hanan Samet |
Publisher | : Morgan Kaufmann |
Total Pages | : 1023 |
Release | : 2006-08-08 |
Genre | : Computers |
ISBN | : 0123694469 |
Author | : Joseph B. Kruskal |
Publisher | : SAGE Publications |
Total Pages | : 100 |
Release | : 1978-01-01 |
Genre | : Social Science |
ISBN | : 1506320880 |
Outlines a set of techniques that enables a researcher to explore the hidden structure of large databases. These techniques use proximities to find a configuration of points that reflect the structure in the data.
Author | : Eldad Davidov |
Publisher | : Routledge |
Total Pages | : 551 |
Release | : 2018-01-31 |
Genre | : Psychology |
ISBN | : 1134991290 |
Intended to bridge the gap between the latest methodological developments and cross-cultural research, this interdisciplinary resource presents the latest strategies for analyzing cross-cultural data. Techniques are demonstrated through the use of applications that employ cross-national data sets such as the latest European Social Survey. With an emphasis on the generalized latent variable approach, internationally prominent researchers from a variety of fields explain how the methods work, how to apply them, and how they relate to other methods presented in the book. Syntax and graphical and verbal explanations of the techniques are included. Online resources, available at www.routledge.com/9781138690271, include some of the data sets and syntax commands used in the book. Applications from the behavioral and social sciences that use real data-sets demonstrate: The use of samples from 17 countries to validate the resistance to change scale across these nations How to test the cross-national invariance properties of social trust The interplay between social structure, religiosity, values, and social attitudes A comparison of anti-immigrant attitudes and patterns of religious orientations across European countries. The second edition includes six new chapters and two revised ones presenting exciting developments in the literature of cross-cultural analysis including topics such as approximate measurement invariance, alignment optimization, sensitivity analyses, a mixed-methods approach to test for measurement invariance, and a multilevel structural equation modeling approach to explain noninvariance. This book is intended for researchers, practitioners, and advanced students interested in cross-cultural research. Because the applications span a variety of disciplines, the book will appeal to researchers and students in: psychology, political science, sociology, education, marketing and economics, geography, criminology, psychometrics, epidemiology, and public health, as well as those interested in methodology. It is also appropriate for an advanced methods course in cross-cultural analysis.
Author | : Jianzhong Wang |
Publisher | : Springer Science & Business Media |
Total Pages | : 363 |
Release | : 2012-04-28 |
Genre | : Computers |
ISBN | : 3642274978 |
"Geometric Structure of High-Dimensional Data and Dimensionality Reduction" adopts data geometry as a framework to address various methods of dimensionality reduction. In addition to the introduction to well-known linear methods, the book moreover stresses the recently developed nonlinear methods and introduces the applications of dimensionality reduction in many areas, such as face recognition, image segmentation, data classification, data visualization, and hyperspectral imagery data analysis. Numerous tables and graphs are included to illustrate the ideas, effects, and shortcomings of the methods. MATLAB code of all dimensionality reduction algorithms is provided to aid the readers with the implementations on computers. The book will be useful for mathematicians, statisticians, computer scientists, and data analysts. It is also a valuable handbook for other practitioners who have a basic background in mathematics, statistics and/or computer algorithms, like internet search engine designers, physicists, geologists, electronic engineers, and economists. Jianzhong Wang is a Professor of Mathematics at Sam Houston State University, U.S.A.
Author | : Konstantinos N. Plataniotis |
Publisher | : Springer Science & Business Media |
Total Pages | : 368 |
Release | : 2013-04-17 |
Genre | : Computers |
ISBN | : 3662041863 |
Reporting the state of the art of colour image processing, this monograph fills a gap in the literature on digital signal and image processing. It contains numerous examples and pictures of colour image processing results, plus a library of algorithms implemented in C.
Author | : Andreas Makrides |
Publisher | : John Wiley & Sons |
Total Pages | : 218 |
Release | : 2020-04-09 |
Genre | : Business & Economics |
ISBN | : 1119721865 |
Data analysis as an area of importance has grown exponentially, especially during the past couple of decades. This can be attributed to a rapidly growing computer industry and the wide applicability of computational techniques, in conjunction with new advances of analytic tools. This being the case, the need for literature that addresses this is self-evident. New publications are appearing, covering the need for information from all fields of science and engineering, thanks to the universal relevance of data analysis and statistics packages. This book is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians who have been working at the forefront of data analysis. The chapters included in this volume represent a cross-section of current concerns and research interests in these scientific areas. The material is divided into two parts: Computational Data Analysis, and Classification Data Analysis, with methods for both - providing the reader with both theoretical and applied information on data analysis methods, models and techniques and appropriate applications.
Author | : Rolf Bader |
Publisher | : Springer |
Total Pages | : 1089 |
Release | : 2018-03-21 |
Genre | : Technology & Engineering |
ISBN | : 3662550040 |
This unique reference book offers a holistic description of the multifaceted field of systematic musicology, which is the study of music, its production and perception, and its cultural, historical and philosophical background. The seven sections reflect the main topics in this interdisciplinary subject. The first two parts discuss musical acoustics and signal processing, comprehensively describing the mathematical and physical fundamentals of musical sound generation and propagation. The complex interplay of physiology and psychology involved in sound and music perception is covered in the following sections, with a particular focus on psychoacoustics and the recently evolved research on embodied music cognition. In addition, a huge variety of technical applications for professional training, music composition and consumer electronics are presented. A section on music ethnology completes this comprehensive handbook. Music theory and philosophy of music are imbedded throughout. Carefully edited and written by internationally respected experts, it is an invaluable reference resource for professionals and graduate students alike.