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Modern multidimensional scaling theory and applications /
"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...
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| Corporate Author: | |
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| Format: | eBook |
| Language: | English |
| Published: |
New York :
Springer,
2005.
New York : 2005. |
| Edition: | 2nd ed. |
| Series: | Springer series in statistics.
|
| Physical Description: |
1 online resource (xxi, 614 pages) : illustrations. |
| Subjects: | |
| Online Access: | SpringerLink - Click here for access |
MARC
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| 100 | 1 | |a Borg, Ingwer. |0 https://id.loc.gov/authorities/names/n78002581. | |
| 245 | 1 | 0 | |a Modern multidimensional scaling : |b theory and applications / |c Ingwer Borg, Patrick J.F. Groenen. |
| 250 | |a 2nd ed. | ||
| 260 | |a New York : |b Springer, |c 2005. | ||
| 264 | 1 | |a New York : |b Springer, |c 2005. | |
| 300 | |a 1 online resource (xxi, 614 pages) : |b illustrations. | ||
| 336 | |a text |b txt |2 rdacontent. | ||
| 337 | |a computer |b c |2 rdamedia. | ||
| 338 | |a online resource |b cr |2 rdacarrier. | ||
| 347 | |a text file. | ||
| 347 | |b PDF. | ||
| 490 | 1 | |a Springer Series in Statistics. | |
| 504 | |a Includes bibliographical references and indexes. | ||
| 520 | 1 | |a "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."--Jacket. | |
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Fundamentals of MDS -- The Four Purposes of Multidimensional Scaling -- Constructing MDS Representations -- MDS Models and Measures of Fit -- Three Applications of MDS -- MDS and Facet Theory -- How to Obtain Proximities -- MDS Models and Solving MDS Problems -- Matrix Algebra for MDS -- A Majorization Algorithm for Solving MDS -- Metric and Nonmetric MDS -- Confirmatory MDS -- MDS Fit Measures, Their Relations, and Some Algorithms -- Classical Scaling -- Special Solutions, Degeneracies, and Local Minima -- Unfolding -- Unfolding -- Avoiding Trivial Solutions in Unfolding -- Special Unfolding Models -- MDS Geometry as a Substantive Model -- MDS as a Psychological Model -- Scalar Products and Euclidean Distances -- Euclidean Embeddings -- MDS and Related Methods -- Procrustes Procedures -- Three-Way Procrustean Models -- Three-Way MDS Models -- Modeling Asymmetric Data -- Methods Related to MDS. | |
| 546 | |a English. | ||
| 506 | |a University staff and students only. Requires University Computer Account login off-campus. | ||
| 650 | 0 | |a Multidimensional scaling. |0 https://id.loc.gov/authorities/subjects/sh85088344. | |
| 650 | 0 | |a Multidimensional scaling |0 https://id.loc.gov/authorities/subjects/sh85088344 |x Data processing. |0 https://id.loc.gov/authorities/subjects/sh99005487. | |
| 650 | 0 | |a Psychometrics. |0 https://id.loc.gov/authorities/subjects/sh85108490. | |
| 650 | 0 | |a Computer algorithms. |0 https://id.loc.gov/authorities/subjects/sh91000149. | |
| 650 | 0 | |a Algorithms. |0 https://id.loc.gov/authorities/subjects/sh85003487. | |
| 650 | 1 | 2 | |a Psychometrics |x methods. |0 https://id.nlm.nih.gov/mesh/D011594Q000379. |
| 650 | 2 | |a Psychometrics. |0 https://id.nlm.nih.gov/mesh/D011594. | |
| 650 | 2 | 2 | |a Data Interpretation, Statistical |0 https://id.nlm.nih.gov/mesh/D003627 |x methods. |
| 650 | 2 | 2 | |a Models, Statistical. |0 https://id.nlm.nih.gov/mesh/D015233. |
| 650 | 2 | 2 | |a Algorithms. |0 https://id.nlm.nih.gov/mesh/D000465. |
| 650 | 6 | |a Échelle multidimensionnelle. | |
| 650 | 6 | |a Échelle multidimensionnelle |x Informatique. | |
| 650 | 6 | |a Psychométrie. | |
| 650 | 6 | |a Algorithmes. | |
| 650 | 7 | |a algorithms. |2 aat. | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x Multivariate Analysis. |2 bisacsh. | |
| 650 | 0 | 7 | |a Mathematical statistics. |2 cct. |
| 650 | 0 | 7 | |a Optical pattern recognition. |2 cct. |
| 650 | 0 | 7 | |a Statistics. |2 cct. |
| 650 | 0 | 7 | |a Marketing. |2 cct. |
| 650 | 0 | 7 | |a Pattern recognition. |2 cct. |
| 650 | 0 | 7 | |a Statistics and Computing/Statistics Programs. |2 cct. |
| 650 | 0 | 7 | |a Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law. |2 cct. |
| 650 | 7 | |a Algoritmos computacionales. |2 embne. | |
| 650 | 0 | 7 | |a Escalas multidimensionales. |2 embucm. |
| 650 | 7 | |a Computer algorithms. |2 fast. | |
| 650 | 7 | |a Algorithms. |2 fast. | |
| 650 | 7 | |a Multidimensional scaling. |2 fast. | |
| 650 | 7 | |a Multidimensional scaling |x Data processing. |2 fast. | |
| 650 | 7 | |a Psychometrics. |2 fast. | |
| 650 | 1 | 7 | |a Multidimensionale schaalmethoden. |2 gtt. |
| 650 | 7 | |a Multivariat analys. |2 sao. | |
| 700 | 1 | |a Groenen, Patrick J. F. |0 https://id.loc.gov/authorities/names/n95003807. | |
| 710 | 2 | |a SpringerLink (Online service) |0 https://id.loc.gov/authorities/names/no2005046756. | |
| 773 | 0 | |t Springer e-books. | |
| 776 | 0 | 8 | |i Print version: |a Borg, Ingwer. |t Modern multidimensional scaling. |b 2nd ed. |d New York : Springer, 2005 |z 0387251502 |z 9780387251509 |w (DLC) 2005924955 |w (OCoLC)61260823. |
| 830 | 0 | |a Springer series in statistics. |0 https://id.loc.gov/authorities/names/n42023188. | |
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