A Characterization of Principal Components for Projection Pursuit
Principal component analysis is a technique often found to be useful for identifying structure in multivariate data. Although it has various characterizations (Rao 1964), the most familiar is as a variance-maximizing projection. Projection pursuit is a methodology for selecting low-dimensional proje...
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| Veröffentlicht in: | The American statistician 1999-05, Vol.53 (2), p.108-109 |
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| container_title | The American statistician |
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| creator | Bolton, Richard J. Krzanowski, Wojtek J. |
| description | Principal component analysis is a technique often found to be useful for identifying structure in multivariate data. Although it has various characterizations (Rao 1964), the most familiar is as a variance-maximizing projection. Projection pursuit is a methodology for selecting low-dimensional projections of multivariate data by the optimization of some index of "interestingness" over all projection directions. Principal component analysis can be viewed as an example of projection pursuit, and we justify its success in structure identification by characterizing it in terms of maximum likelihood under the assumption of normality. |
| doi_str_mv | 10.1080/00031305.1999.10474441 |
| format | Article |
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Characterization of Principal Components for Projection Pursuit</title><author>Bolton, Richard J. ; Krzanowski, Wojtek J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c339t-25a3c8f144bdd660e9e6f2c33197230cc0d0c5008d1d6ff4cac8ffd233b5542d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1999</creationdate><topic>Data analysis</topic><topic>Dimension reduction</topic><topic>Exact sciences and technology</topic><topic>Exploratory data analysis</topic><topic>Graphical projections</topic><topic>Mathematics</topic><topic>Maximized likelihood</topic><topic>Multivariate analysis</topic><topic>Non-normality</topic><topic>Optimization</topic><topic>Principal components analysis</topic><topic>Probability and statistics</topic><topic>Sciences and techniques of general use</topic><topic>Skewed distribution</topic><topic>Skewness</topic><topic>Software</topic><topic>Statistical 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| ispartof | The American statistician, 1999-05, Vol.53 (2), p.108-109 |
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| language | eng |
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| source | Jstor Complete Legacy; Periodicals Index Online; JSTOR Mathematics & Statistics |
| subjects | Data analysis Dimension reduction Exact sciences and technology Exploratory data analysis Graphical projections Mathematics Maximized likelihood Multivariate analysis Non-normality Optimization Principal components analysis Probability and statistics Sciences and techniques of general use Skewed distribution Skewness Software Statistical variance Statistics |
| title | A Characterization of Principal Components for Projection Pursuit |
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