| get_mca | R Documentation |
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
For FactoMineR MCA results, get_mca() and get_mca_var() also
support element = "quanti.sup" for quantitative supplementary
variables and report a clean package-level error when that result is
absent.
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)
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, and "quanti.sup" for quantitative supplementary variables in FactoMineR MCA results. |
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 |
Alboukadel Kassambara alboukadel.kassambara@gmail.com
https://www.sthda.com/english/
# Multiple Correspondence Analysis
# ++++++++++++++++++++++++++++++
# Install and load FactoMineR to compute MCA
# install.packages("FactoMineR")
library("FactoMineR")
data(poison)
res.mca <- MCA(poison, quanti.sup = 1:2, 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
quanti.sup <- get_mca(res.mca, "quanti.sup")
head(quanti.sup$coord) # coordinates of quantitative supplementary variables
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.