| summary_pca_centralities {CINNA} | R Documentation |
Summarize PCA result related to centrality measures
Description
This function summarizes the PCA result related to centrality measures.
Usage
summary_pca_centralities(x, scale.unit = TRUE, ncp = 5)
Arguments
x |
A list containing the computed centrality values. |
scale.unit |
A boolean value indicating whether the data should be scaled to unit variance (default = TRUE). |
ncp |
The number of dimensions in the final results (default = 5). |
Value
The result of the pca_centralities function, which includes the PCA analysis results such as eigenvalues, variance explained, and scores.
The returned value is an object of class "PCA" from the FactoMineR package. It contains the following components:
eig |
A numeric vector of eigenvalues, indicating the amount of variance explained by each principal component. |
var |
A numeric vector of proportions of variance explained by each principal component. |
ind |
A data frame of individual scores, where each row represents an individual and each column represents a principal component. |
call |
The function call used to create the PCA object. |
call2 |
The call used to compute the PCA analysis. |
call3 |
The call used to project the individuals. |
svd |
The singular value decomposition of the data matrix. |
cor |
The correlation matrix of the variables. |
cos2 |
The squared cosines of the variables. |
contrib |
The contributions of the variables to the principal components. |
proj |
The projected coordinates of the individuals on the principal components. |
quali.sup |
The results of the supplementary qualitative variables analysis. |
quali.sup.ind |
The results of the supplementary individuals analysis. |
quanti.sup |
The results of the supplementary quantitative variables analysis. |
quanti.sup.var |
The results of the supplementary variables analysis. |
Author(s)
Minoo Ashtiani, Mehdi Mirzaie, Mohieddin Jafari