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Titlebook: Modern Multidimensional Scaling; Theory and Applicati Ingwer Borg,Patrick J. F. Groenen Book 2005Latest edition Springer-Verlag New York 20

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發(fā)表于 2025-3-21 19:07:06 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Modern Multidimensional Scaling
副標(biāo)題Theory and Applicati
編輯Ingwer Borg,Patrick J. F. Groenen
視頻videohttp://file.papertrans.cn/638/637293/637293.mp4
概述Second edition of a successful book.Provides an up-to-date comprehensive treatment of multidimensional scaling (MDS), a statistical technique used to analyze the structure of similarity or dissimilari
叢書名稱Springer Series in Statistics
圖書封面Titlebook: Modern Multidimensional Scaling; Theory and Applicati Ingwer Borg,Patrick J. F. Groenen Book 2005Latest edition Springer-Verlag New York 20
描述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 reade
出版日期Book 2005Latest edition
關(guān)鍵詞algorithms; best fit; correlation; marketing; modeling; multidimensional scaling; statistics
版次2
doihttps://doi.org/10.1007/0-387-28981-X
isbn_softcover978-1-4419-2046-1
isbn_ebook978-0-387-28981-6Series ISSN 0172-7397 Series E-ISSN 2197-568X
issn_series 0172-7397
copyrightSpringer-Verlag New York 2005
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發(fā)表于 2025-3-21 21:33:13 | 只看該作者
0172-7397 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 reade978-1-4419-2046-1978-0-387-28981-6Series ISSN 0172-7397 Series E-ISSN 2197-568X
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978-1-4419-2046-1Springer-Verlag New York 2005
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Modern Multidimensional Scaling978-0-387-28981-6Series ISSN 0172-7397 Series E-ISSN 2197-568X
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https://doi.org/10.1007/0-387-28981-Xalgorithms; best fit; correlation; marketing; modeling; multidimensional scaling; statistics
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0172-7397 e used to analyze the structure of similarity or dissimilariMultidimensionalscaling(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 forasetofcountri
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2363-6149 .Is written by an expert with over 43 years of teaching expe.This is the second in a series of three volumes dealing with important topics in algebra. Volume 2 is an introduction to linear algebra (including linear algebra over rings), Galois theory, representation theory, and the theory of group ex
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