Multivariate analysis of mixed data: The PCAmixdata R package

Marie Chavent 1, 2
1 CQFD - Quality control and dynamic reliability
IMB - Institut de Mathématiques de Bordeaux, Inria Bordeaux - Sud-Ouest
Abstract : Mixed data type arise when observations are described by a mixture of numerical and categorical variables. The R package PCAmixdata extends standard multivariate analysis methods to incorporate this type of data. The key techniques included in the package are PCAmix (PCA of a mixture of numerical and categorical variables), PCArot (rotation in PCAmix) and MFAmix (multiple factor analysis with mixed data within a dataset). A synthetic presentation of the three algorithms will be provided and the three main procedures will be illustrated on real data composed of four datasets caracterizing conditions of life of cities of Gironde, a south-west region of France.
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Conference papers
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Submitted on : Wednesday, December 14, 2016 - 5:49:44 PM
Last modification on : Thursday, January 11, 2018 - 6:22:11 AM


  • HAL Id : hal-01416742, version 1



Marie Chavent. Multivariate analysis of mixed data: The PCAmixdata R package. 9th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2016) , Dec 2016, Seville, Spain. 〈hal-01416742〉



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