Modern Multidimensional Scaling: Theory and Applications
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer New York
1997
|
| Schriftenreihe: | Springer Series in Statistics
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| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | 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 |
| Beschreibung: | 1 Online-Ressource (XVII, 472 p) |
| ISBN: | 9781475727111 9781475727135 |
| ISSN: | 0172-7397 |
| DOI: | 10.1007/978-1-4757-2711-1 |
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| dewey-full | 519.5 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
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| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4757-2711-1 |
| format | Electronic eBook |
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| isbn | 9781475727111 9781475727135 |
| issn | 0172-7397 |
| language | English |
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| spelling | Borg, Ingwer Verfasser aut Modern Multidimensional Scaling Theory and Applications by Ingwer Borg, Patrick Groenen New York, NY Springer New York 1997 1 Online-Ressource (XVII, 472 p) txt rdacontent c rdamedia cr rdacarrier Springer Series in Statistics 0172-7397 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 Statistics Statistics, general Statistik Multidimensionale Skalierung (DE-588)4075090-5 gnd rswk-swf Multidimensionale Skalierung (DE-588)4075090-5 s 1\p DE-604 Groenen, Patrick Sonstige oth https://doi.org/10.1007/978-1-4757-2711-1 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Borg, Ingwer Modern Multidimensional Scaling Theory and Applications Statistics Statistics, general Statistik Multidimensionale Skalierung (DE-588)4075090-5 gnd |
| subject_GND | (DE-588)4075090-5 |
| title | Modern Multidimensional Scaling Theory and Applications |
| title_auth | Modern Multidimensional Scaling Theory and Applications |
| title_exact_search | Modern Multidimensional Scaling Theory and Applications |
| title_full | Modern Multidimensional Scaling Theory and Applications by Ingwer Borg, Patrick Groenen |
| title_fullStr | Modern Multidimensional Scaling Theory and Applications by Ingwer Borg, Patrick Groenen |
| title_full_unstemmed | Modern Multidimensional Scaling Theory and Applications by Ingwer Borg, Patrick Groenen |
| title_short | Modern Multidimensional Scaling |
| title_sort | modern multidimensional scaling theory and applications |
| title_sub | Theory and Applications |
| topic | Statistics Statistics, general Statistik Multidimensionale Skalierung (DE-588)4075090-5 gnd |
| topic_facet | Statistics Statistics, general Statistik Multidimensionale Skalierung |
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