PCA-class: PCA Results

In dimensio: Multivariate Data Analysis

PCA Results

Description

An S4 class to store the results of a principal components analysis.

Slots

center

A numeric vector giving the column mean of the initial dataset (active individuals only).

scale

A numeric vector giving the column standard deviations of the initial dataset (active individuals only).

Note

This class inherits from MultivariateAnalysis.

Author(s)

N. Frerebeau

See Also

Other class: BootstrapCA-class, BootstrapPCA-class, CA-class, MCA-class, MultivariateAnalysis, MultivariateBootstrap, MultivariateResults, MultivariateSummary, PCOA-class

Examples

## Load data
data("iris")

## Compute principal components analysis
X <- pca(iris, sup_quali = "Species")

## Get eigenvalues
get_eigenvalues(X)

## Get individual cos2
head(get_cos2(X, margin = 1))

## Get variable contributions
get_contributions(X, margin = 2)

## Get correlations between variables and dimensions
get_correlations(X)

dimensio documentation built on April 3, 2025, 10:36 p.m.