condes

a data frame made up of at least one quantitative variable and a set of quantitative variables and/or categorical variables

donnee

the number of the variable to characterized

num.var

weights for the individuals; if NULL, all individuals has a weight equals to 1; the sum of the weights can be equal to 1 and then the weights will be multiplied by the number of individuals, the sum can be greater than the number of individuals

weights

the significance threshold considered to characterized the category (by default 0.05)

proba


Description continuous by quantitative variables and/or by categorical variables


multivariate

Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis.

condes: Continuous variable description

Description

Usage

Arguments

Value

See Also

Examples