Multivariate analysis of mixed data: The PCAmixdata R package
| 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 | Environnement, territoires et infrastructures [UR ETBX] | |
| dc.contributor.author | KUENTZ, Vanessa | |
| hal.structure.identifier | Environnement, territoires et infrastructures [UR ETBX] | |
| dc.contributor.author | LABENNE, Amaury | |
| hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
| hal.structure.identifier | Quality control and dynamic reliability [CQFD] | |
| hal.structure.identifier | Ecole Nationale Supérieure de Cognitique [ENSC] | |
| dc.contributor.author | SARACCO, Jerome | |
| dc.date.accessioned | 2024-04-04T03:16:37Z | |
| dc.date.available | 2024-04-04T03:16:37Z | |
| dc.date.conference | 2015-06-30 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/194231 | |
| dc.description.abstractEn | 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. | |
| dc.language.iso | en | |
| dc.subject.en | mixture of numerical and categorical variables | |
| dc.subject.en | Multivariate data analysis | |
| dc.subject.en | rotation | |
| dc.subject.en | multi-group data | |
| dc.subject.en | principal component analysis | |
| dc.title.en | Multivariate analysis of mixed data: The PCAmixdata R package | |
| dc.type | Communication dans un congrès | |
| dc.subject.hal | Statistiques [stat] | |
| dc.subject.hal | Statistiques [stat]/Machine Learning [stat.ML] | |
| bordeaux.hal.laboratories | Institut de Mathématiques de Bordeaux (IMB) - UMR 5251 | * |
| bordeaux.institution | Université de Bordeaux | |
| bordeaux.institution | Bordeaux INP | |
| bordeaux.institution | CNRS | |
| bordeaux.conference.title | The useR! Conference 2015 | |
| bordeaux.country | DK | |
| bordeaux.conference.city | Aalborg | |
| bordeaux.peerReviewed | oui | |
| hal.identifier | hal-01246858 | |
| hal.version | 1 | |
| hal.invited | non | |
| hal.proceedings | non | |
| hal.popular | non | |
| hal.audience | Internationale | |
| hal.origin.link | https://hal.archives-ouvertes.fr//hal-01246858v1 | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=CHAVENT,%20Marie&KUENTZ,%20Vanessa&LABENNE,%20Amaury&SARACCO,%20Jerome&rft.genre=unknown |
Fichier(s) constituant ce document
| Fichiers | Taille | Format | Vue |
|---|---|---|---|
|
Il n'y a pas de fichiers associés à ce document. |
|||