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Last data update: 2014.03.03

R: Dual Multiple Factor Analysis (DMFA)

DMFA	R Documentation

Dual Multiple Factor Analysis (DMFA)

Description

Performs Dual Multiple Factor Analysis (DMFA) with supplementary individuals, supplementary quantitative variables and supplementary categorical variables.

Usage

DMFA(don, num.fact = ncol(don), scale.unit = TRUE, ncp = 5, 
    quanti.sup = NULL, quali.sup = NULL, graph = TRUE, axes=c(1,2))

Arguments

`don`	a data frame with n rows (individuals) and p columns (numeric variables)
`num.fact`	the number of the categorical variable which allows to make the group of individuals
`scale.unit`	a boolean, if TRUE (value set by default) then data are scaled to unit variance
`ncp`	number of dimensions kept in the results (by default 5)
`quanti.sup`	a vector indicating the indexes of the quantitative supplementary variables
`quali.sup`	a vector indicating the indexes of the categorical supplementary variables
`graph`	boolean, if TRUE a graph is displayed
`axes`	a length 2 vector specifying the components to plot

Value

Returns a list including:

`eig`	a matrix containing all the eigenvalues, the percentage of variance and the cumulative percentage of variance
`var`	a list of matrices containing all the results for the active variables (coordinates, correlation between variables and axes, square cosine, contributions)
`ind`	a list of matrices containing all the results for the active individuals (coordinates, square cosine, contributions)
`ind.sup`	a list of matrices containing all the results for the supplementary individuals (coordinates, square cosine)
`quanti.sup`	a list of matrices containing all the results for the supplementary quantitative variables (coordinates, correlation between variables and axes)
`quali.sup`	a list of matrices containing all the results for the supplementary categorical variables (coordinates of each categories of each variables, and v.test which is a criterion with a Normal distribution)
`svd`	the result of the singular value decomposition
`var.partiel`	a list with the partial coordinate of the variables for each group
`cor.dim.gr`
`Xc`	a list with the data centered by group
`group`	a list with the results for the groups (cordinate, normalized coordinates, cos2)
`Cov`	a list with the covariance matrices for each group

Returns the individuals factor map and the variables factor map.

Author(s)

Francois Husson Francois.Husson@agrocampus-ouest.fr

Examples

## Example with the famous Fisher's iris data
res.dmfa = DMFA ( iris, num.fact = 5)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(FactoMineR)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/FactoMineR/DMFA.Rd_%03d_medium.png", width=480, height=480)
> ### Name: DMFA
> ### Title: Dual Multiple Factor Analysis (DMFA)
> ### Aliases: DMFA
> ### Keywords: multivariate
> 
> ### ** Examples
> 
> ## Example with the famous Fisher's iris data
> res.dmfa = DMFA ( iris, num.fact = 5)
dev.new(): using pdf(file="Rplots893.pdf")
dev.new(): using pdf(file="Rplots894.pdf")
dev.new(): using pdf(file="Rplots895.pdf")
dev.new(): using pdf(file="Rplots896.pdf")
> 
> 
> 
> 
> 
> dev.off()
png 
  2 
>