方法对比
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| 双标图：多元数据中行和列的同时显示× | 多维尺度分析 (MDS)× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 1971 | 1952–1964 |
| 提出者≠ | Ruben Gabriel | Warren S. Torgerson (metric MDS, 1952); Joseph B. Kruskal (non-metric MDS, 1964) |
| 类型≠ | Multivariate graphical display | Dimensionality reduction / visualization |
| 开创性文献≠ | Gabriel, K. R. (1971). The biplot graphic display of matrices with application to principal component analysis. Biometrika, 58(3), 453–467. DOI ↗ | Kruskal, J. B. (1964). Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika, 29(1), 1–27. DOI ↗ |
| 别名 | Gabriel biplot, PCA biplot, JK biplot, Çift grafik | MDS, metric MDS, non-metric MDS, proximity scaling |
| 相关≠ | 2 | 5 |
| 摘要≠ | A biplot is a low-dimensional graphical representation of a multivariate data matrix that simultaneously displays both the observations (rows) and the variables (columns) as points or vectors in the same plot. Introduced by Ruben Gabriel in 1971, the technique decomposes the data matrix into a rank-2 approximation using singular value decomposition, allowing the approximate value of any data entry to be read as the inner product of the corresponding row and column markers. | Multidimensional scaling maps objects described only by pairwise similarities or dissimilarities into a low-dimensional geometric space so that distances in that space reflect the original proximity structure as faithfully as possible. It is widely used to visualize the hidden structure of psychological, social, and behavioral data. |
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