Orthogonal rotation in PCAMIX
hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
hal.structure.identifier | Quality control and dynamic reliability [CQFD] | |
dc.contributor.author | CHAVENT, Marie | |
hal.structure.identifier | Aménités et dynamiques des espaces ruraux [UR ADBX] | |
dc.contributor.author | VANESSA, K. | |
hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
hal.structure.identifier | Quality control and dynamic reliability [CQFD] | |
dc.contributor.author | SARACCO, Jérôme | |
dc.date.accessioned | 2024-04-04T02:23:38Z | |
dc.date.available | 2024-04-04T02:23:38Z | |
dc.date.created | 2011-12-01 | |
dc.date.issued | 2012 | |
dc.identifier.issn | 1862-5347 | |
dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/189751 | |
dc.description.abstractEn | Kiers (1991) considered the orthogonal rotation in PCAMIX, a principal component method for a mixture of qualitative and quantitative variables. PCAMIX includes the ordinary principal component analysis (PCA) and multiple correspondence analysis (MCA) as special cases. In this paper, we give a new presentation of PCAMIX where the principal components and the squared loadings are obtained from a Singular Value Decomposition. The loadings of the quantitative variables and the principal coordinates of the categories of the qualitative variables are also obtained directly. In this context, we propose a computationaly efficient procedure for varimax rotation in PCAMIX and a direct solution for the optimal angle of rotation. A simulation study shows the good computational behavior of the proposed algorithm. An application on a real data set illustrates the interest of using rotation in MCA. All source codes are available in the R package "PCAmixdata". | |
dc.language.iso | en | |
dc.publisher | Springer Verlag | |
dc.subject.en | MIXTURE OF QUALITATIVE AND QUANTITATIVE DATA MULTIPLE CORRESPONDENCE ANALYSIS | |
dc.title.en | Orthogonal rotation in PCAMIX | |
dc.type | Article de revue | |
dc.identifier.doi | 10.1007/s11634-012-0105-3 | |
dc.subject.hal | Statistiques [stat]/Calcul [stat.CO] | |
dc.identifier.arxiv | 1112.0301 | |
bordeaux.journal | Advances in Data Analysis and Classification | |
bordeaux.page | 131-146 | |
bordeaux.volume | 6 | |
bordeaux.hal.laboratories | Institut de Mathématiques de Bordeaux (IMB) - UMR 5251 | * |
bordeaux.institution | Université de Bordeaux | |
bordeaux.institution | Bordeaux INP | |
bordeaux.institution | CNRS | |
bordeaux.peerReviewed | oui | |
hal.identifier | hal-00764427 | |
hal.version | 1 | |
hal.popular | non | |
hal.audience | Internationale | |
hal.origin.link | https://hal.archives-ouvertes.fr//hal-00764427v1 | |
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