FactoMineR: AnRPackage for Multivariate Analysis | Zendy

Sébastien Lê | Zendy; Julie Josse | Zendy; François Husson | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

FactoMineR: AnRPackage for Multivariate Analysis

Author(s) -

Sébastien Lê,

Julie Josse,

François Husson

Publication year - 2008

Publication title -

journal of statistical software

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 7.636

H-Index - 145

ISSN - 1548-7660

DOI - 10.18637/jss.v025.i01

Subject(s) - categorical variable , r package , computer science , multivariate statistics , partition (number theory) , graphics , hierarchy , statistical graphics , exploratory data analysis , data mining , multivariate analysis , mathematics , programming language , machine learning , computer graphics (images) , combinatorics , economics , market economy

In this article, we present FactoMineR an R package dedicated to multivariate data analysis. The main features of this package is the possibility to take into account dierent types of variables (quantitative or categorical), dierent types of structure on the data (a partition on the variables, a hierarchy on the variables, a partition on the individuals) and nally supplementary information (supplementary individuals and variables). Moreover, the dimensions issued from the dierent exploratory data analyses can be automatically described by quantitative and/or categorical variables. Numerous graphics are also avail- able with various options. Finally, a graphical user interface is implemented within the Rcmdr environment in order to propose an user friendly package.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research