Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Кореспондентний аналіз× | Біблóт: Одночасне відображення рядків і стовпців у багатовимірних даних× | |
|---|---|---|
| Галузь | Статистика | Статистика |
| Родина | Latent structure | Latent structure |
| Рік появи≠ | 1984 | 1971 |
| Автор методу≠ | Jean-Paul Benzécri; Michael Greenacre | Ruben Gabriel |
| Тип≠ | Exploratory multivariate technique for categorical data | Multivariate graphical display |
| Основоположне джерело≠ | Greenacre, M. J. (1984). Theory and Applications of Correspondence Analysis. Academic Press. ISBN: 978-0-12-299050-2 | Gabriel, K. R. (1971). The biplot graphic display of matrices with application to principal component analysis. Biometrika, 58(3), 453–467. DOI ↗ |
| Інші назви | CA, Simple Correspondence Analysis, Reciprocal Averaging, Karşılıklı Uyum Analizi | Gabriel biplot, PCA biplot, JK biplot, Çift grafik |
| Пов'язані | 2 | 2 |
| Підсумок≠ | Correspondence Analysis (CA) is an exploratory multivariate technique for visualizing the association structure of a two-way contingency table. Developed systematically by Jean-Paul Benzécri in France during the 1960s–1970s and brought to an English-language audience by Michael Greenacre in 1984, CA decomposes the chi-square statistic of a cross-tabulation to produce a low-dimensional joint display — called a biplot — in which rows and columns are represented as points whose proximities reflect their associations. | 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. |
| ScholarGateНабір даних ↗ |
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