calculateLoadingsContribution {psichomics} | R Documentation

## Calculate the contribution of PCA loadings to the selected principal components

### Description

Total contribution of a variable is calculated as per `((Cx * Ex) + (Cy * Ey))/(Ex + Ey)`, where:

- `Cx` and `Cy` are the contributions of a variable to principal components `x` and `y`

- `Ex` and `Ey` are the eigenvalues of principal components `x` and `y`

### Usage

    calculateLoadingsContribution(pca, pcX = 1, pcY = 2)

### Arguments

`pca` | `prcomp` object
`pcX` | Character: name of the X axis of interest from the PCA
`pcY` | Character: name of the Y axis of interest from the PCA

### Value

Data frame containing the correlation between variables and selected principal components and the contribution of variables to the selected principal components (both individual and total contribution)

### Source

http://www.sthda.com/english/articles/31-principal-component-methods-in-r-practical-guide/112-pca-principal-component-analysis-essentials/

### See Also

Other functions to analyse principal components: `performPCA()`, `plotPCAvariance()`, `plotPCA()`

### Examples

    pca <- performPCA(USArrests)
    calculateLoadingsContribution(pca)

[Package psichomics version 1.16.0 Index]