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| Robustná viacnásobná korešpondenčná analýza (Robustná MCA)× | Korešpondenčná analýza× | |
|---|---|---|
| Odbor | Štatistika | Štatistika |
| Rodina | Latent structure | Latent structure |
| Rok vzniku≠ | 2000s | 1984 |
| Tvorca≠ | Extensions by Hubert, Rousseeuw and collaborators; building on classical MCA by Benzécri (1973) and Greenacre (1984) | Jean-Paul Benzécri; Michael Greenacre |
| Typ≠ | Robust multivariate dimension reduction | Exploratory multivariate technique for categorical data |
| Pôvodný zdroj≠ | Greenacre, M. J. (2017). Correspondence Analysis in Practice (3rd ed.). Chapman & Hall / CRC Press, Boca Raton. ISBN: 978-1498731775 | Greenacre, M. J. (1984). Theory and Applications of Correspondence Analysis. Academic Press. ISBN: 978-0-12-299050-2 |
| Ďalšie názvy≠ | Robust MCA, Outlier-resistant MCA, Robust HOMALS | CA, Simple Correspondence Analysis, Reciprocal Averaging, Karşılıklı Uyum Analizi |
| Príbuzné≠ | 4 | 2 |
| Zhrnutie≠ | Robust Multiple Correspondence Analysis extends classical MCA to datasets containing outlying or atypical rows of categorical data. By downweighting influential observations before the singular value decomposition, it produces a low-dimensional map of category relationships that faithfully represents the bulk of the data rather than being distorted by a handful of anomalous cases. | 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. |
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