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Modern Multidimensional Scaling: Theory and Applications
Contributor(s): Borg, I. (Author), Groenen, P. J. F. (Author)
ISBN: 1441920463     ISBN-13: 9781441920461
Publisher: Springer
OUR PRICE:   $237.49  
Product Type: Paperback - Other Formats
Published: November 2010
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Additional Information
BISAC Categories:
- Social Science | Statistics
- Computers | Computer Vision & Pattern Recognition
- Mathematics | Probability & Statistics - General
Dewey: 519.535
Series: Springer Series in Statistics
Physical Information: 1.28" H x 6.14" W x 9.21" (1.94 lbs) 614 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
Multidimensionalscaling(MDS)isatechniquefortheanalysisofsimilarity 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 forasetofcountries.MDSattemptstomodelsuchdataasdistancesamong pointsinageometricspace.Themainreasonfordoingthisisthatonewants 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 mapthedata, themappingfunction, thealgorithmsusedto?ndanoptimal 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 di?erent purposes for which MDS has been used, to various ways of looking at or "interpreting" an MDS representation, or to di?erences in the data required for the particular models. Inthisbook, wegiveafairlycomprehensivepresentationofMDS.Forthe reader with applied interests only, the ?rst six chapters of Part I should be su?cient. They explain the basic notions of ordinary MDS, with an emphasis on how MDS can be helpful in answering substantive questions.