Principal Component Analysis:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer New York
1986
|
| Schriftenreihe: | Springer Series in Statistics
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | Principal component analysis is probably the oldest and best known of the It was first introduced by Pearson (1901), techniques ofmultivariate analysis. and developed independently by Hotelling (1933). Like many multivariate methods, it was not widely used until the advent of electronic computers, but it is now weIl entrenched in virtually every statistical computer package. The central idea of principal component analysis is to reduce the dimen sionality of a data set in which there are a large number of interrelated variables, while retaining as much as possible of the variation present in the data set. This reduction is achieved by transforming to a new set of variables, the principal components, which are uncorrelated, and which are ordered so that the first few retain most of the variation present in all of the original variables. Computation of the principal components reduces to the solution of an eigenvalue-eigenvector problem for a positive-semidefinite symmetrie matrix. Thus, the definition and computation of principal components are straightforward but, as will be seen, this apparently simple technique has a wide variety of different applications, as weIl as a number of different deri vations. Any feelings that principal component analysis is a narrow subject should soon be dispelled by the present book; indeed some quite broad topics which are related to principal component analysis receive no more than a brief mention in the final two chapters |
| Beschreibung: | 1 Online-Ressource (XIII, 271 p) |
| ISBN: | 9781475719048 9781475719062 |
| ISSN: | 0172-7397 |
| DOI: | 10.1007/978-1-4757-1904-8 |
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Datensatz im Suchindex
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| author_sort | Jolliffe, I. T. |
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| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4757-1904-8 |
| format | Electronic eBook |
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| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:21:08Z |
| institution | BVB |
| isbn | 9781475719048 9781475719062 |
| issn | 0172-7397 |
| language | English |
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| spelling | Jolliffe, I. T. Verfasser aut Principal Component Analysis by I. T. Jolliffe New York, NY Springer New York 1986 1 Online-Ressource (XIII, 271 p) txt rdacontent c rdamedia cr rdacarrier Springer Series in Statistics 0172-7397 Principal component analysis is probably the oldest and best known of the It was first introduced by Pearson (1901), techniques ofmultivariate analysis. and developed independently by Hotelling (1933). Like many multivariate methods, it was not widely used until the advent of electronic computers, but it is now weIl entrenched in virtually every statistical computer package. The central idea of principal component analysis is to reduce the dimen sionality of a data set in which there are a large number of interrelated variables, while retaining as much as possible of the variation present in the data set. This reduction is achieved by transforming to a new set of variables, the principal components, which are uncorrelated, and which are ordered so that the first few retain most of the variation present in all of the original variables. Computation of the principal components reduces to the solution of an eigenvalue-eigenvector problem for a positive-semidefinite symmetrie matrix. Thus, the definition and computation of principal components are straightforward but, as will be seen, this apparently simple technique has a wide variety of different applications, as weIl as a number of different deri vations. Any feelings that principal component analysis is a narrow subject should soon be dispelled by the present book; indeed some quite broad topics which are related to principal component analysis receive no more than a brief mention in the final two chapters Statistics Statistics, general Statistik Hauptkomponentenanalyse (DE-588)4129174-8 gnd rswk-swf Faktorenanalyse (DE-588)4016338-6 gnd rswk-swf Multivariate Analyse (DE-588)4040708-1 gnd rswk-swf Faktorenanalyse (DE-588)4016338-6 s 1\p DE-604 Hauptkomponentenanalyse (DE-588)4129174-8 s 2\p DE-604 Multivariate Analyse (DE-588)4040708-1 s 3\p DE-604 https://doi.org/10.1007/978-1-4757-1904-8 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Jolliffe, I. T. Principal Component Analysis Statistics Statistics, general Statistik Hauptkomponentenanalyse (DE-588)4129174-8 gnd Faktorenanalyse (DE-588)4016338-6 gnd Multivariate Analyse (DE-588)4040708-1 gnd |
| subject_GND | (DE-588)4129174-8 (DE-588)4016338-6 (DE-588)4040708-1 |
| title | Principal Component Analysis |
| title_auth | Principal Component Analysis |
| title_exact_search | Principal Component Analysis |
| title_full | Principal Component Analysis by I. T. Jolliffe |
| title_fullStr | Principal Component Analysis by I. T. Jolliffe |
| title_full_unstemmed | Principal Component Analysis by I. T. Jolliffe |
| title_short | Principal Component Analysis |
| title_sort | principal component analysis |
| topic | Statistics Statistics, general Statistik Hauptkomponentenanalyse (DE-588)4129174-8 gnd Faktorenanalyse (DE-588)4016338-6 gnd Multivariate Analyse (DE-588)4040708-1 gnd |
| topic_facet | Statistics Statistics, general Statistik Hauptkomponentenanalyse Faktorenanalyse Multivariate Analyse |
| url | https://doi.org/10.1007/978-1-4757-1904-8 |
| work_keys_str_mv | AT jolliffeit principalcomponentanalysis |