| get_mca {factoextra} | R Documentation |
Extract the results for individuals/variables - MCA
Description
Extract all the results (coordinates, squared cosine and
contributions) for the active individuals/variable categories from Multiple
Correspondence Analysis (MCA) outputs.
get_mca(): Extract the results for variables and individuals
get_mca_ind(): Extract the results for individuals only
get_mca_var(): Extract the results for variables only
Usage
get_mca(res.mca, element = c("var", "ind", "mca.cor", "quanti.sup"))
get_mca_var(res.mca, element = c("var", "mca.cor", "quanti.sup"))
get_mca_ind(res.mca)
Arguments
res.mca |
an object of class MCA [FactoMineR], acm [ade4], expoOutput/epMCA [ExPosition]. |
element |
the element to subset from the output. Possible values are "var" for variables, "ind" for individuals, "mca.cor" for correlation between variables and principal dimensions, "quanti.sup" for quantitative supplementary variables. |
Value
a list of matrices containing the results for the active individuals/variable categories including :
coord |
coordinates for the individuals/variable categories |
cos2 |
cos2 for the individuals/variable categories |
contrib |
contributions of the individuals/variable categories |
inertia |
inertia of the individuals/variable categories |
Author(s)
Alboukadel Kassambara alboukadel.kassambara@gmail.com
References
http://www.sthda.com/english/
Examples
# Multiple Correspondence Analysis
# ++++++++++++++++++++++++++++++
# Install and load FactoMineR to compute MCA
# install.packages("FactoMineR")
library("FactoMineR")
data(poison)
poison.active <- poison[1:55, 5:15]
head(poison.active[, 1:6])
res.mca <- MCA(poison.active, graph=FALSE)
# Extract the results for variable categories
var <- get_mca_var(res.mca)
print(var)
head(var$coord) # coordinates of variables
head(var$cos2) # cos2 of variables
head(var$contrib) # contributions of variables
# Extract the results for individuals
ind <- get_mca_ind(res.mca)
print(ind)
head(ind$coord) # coordinates of individuals
head(ind$cos2) # cos2 of individuals
head(ind$contrib) # contributions of individuals
# You can also use the function get_mca()
get_mca(res.mca, "ind") # Results for individuals
get_mca(res.mca, "var") # Results for variable categories