get_pca {factoextra} | R Documentation |
Extract all the results (coordinates, squared cosine, contributions) for
the active individuals/variables from Principal Component Analysis (PCA) outputs.
get_pca(): Extract the results for variables and individuals
get_pca_ind(): Extract the results for individuals only
get_pca_var(): Extract the results for variables only
get_pca(res.pca, element = c("var", "ind")) get_pca_ind(res.pca, ...) get_pca_var(res.pca)
res.pca |
an object of class PCA [FactoMineR]; prcomp and princomp [stats]; pca, dudi [adea4]; epPCA [ExPosition]. |
element |
the element to subset from the output. Allowed values are "var" (for active variables) or "ind" (for active individuals). |
... |
not used |
a list of matrices containing all the results for the active individuals/variables including:
coord |
coordinates for the individuals/variables |
cos2 |
cos2 for the individuals/variables |
contrib |
contributions of the individuals/variables |
Alboukadel Kassambara alboukadel.kassambara@gmail.com
http://www.sthda.com/english/
# Principal Component Analysis # +++++++++++++++++++++++++++++ data(iris) res.pca <- prcomp(iris[, -5], scale = TRUE) # Extract the results for individuals ind <- get_pca_ind(res.pca) print(ind) head(ind$coord) # coordinates of individuals head(ind$cos2) # cos2 of individuals head(ind$contrib) # contributions of individuals # Extract the results for variables var <- get_pca_var(res.pca) print(var) head(var$coord) # coordinates of variables head(var$cos2) # cos2 of variables head(var$contrib) # contributions of variables # You can also use the function get_pca() get_pca(res.pca, "ind") # Results for individuals get_pca(res.pca, "var") # Results for variable categories