| 来源类型 | Article
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| 规范类型 | 其他
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| DOI | 10.1016/S0167-9473(97)00038-8
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| Ordinal principal component analysis theory and an application. |
| Korhonen P; Siljamaeki A
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| 发表日期 | 1998
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| 出处 | Computational Statistics & Data Analysis 26 (4): 411-424
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| 出版年 | 1998
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| 语种 | 英语
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| 摘要 | In this study we investigate the problem of ordering multivariate data. We propose the use of the so-called (first) ordinal principal component for this purpose. The ordinal principal component is defined as a new ordinal variable which orders the sample observations in such a way that the sum of the squares of the (rank) correlation coefficients between the original variables and the ordinal principal component is maximal. The definition provides a direct way to estimate a rank order for multivariate observations and it is also applicable to varibles measured only on ordinal scales. It is consistent with the usual definition of the principal component transformation in the sense that the sum of the (weighted) squares of the correlation coefficients between the original variables and the principal component is also maximal. Because the correlation coefficients (Spearman's and Kendall's rank correlation coefficients) can be defined for ordinal variables as well, the ordinal principal component can be defined without using any cardinal information. |
| 主题 | Decision Analysis and Support (DAS)
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| URL | http://pure.iiasa.ac.at/id/eprint/5374/
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| 来源智库 | International Institute for Applied Systems Analysis (Austria)
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| 引用统计 |
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| 资源类型 | 智库出版物
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| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/127731
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推荐引用方式
GB/T 7714 |
Korhonen P,Siljamaeki A. Ordinal principal component analysis theory and an application.. 1998.
|
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