Understanding Principal Component Analysis (PCA) Results for Dimensionality Reduction: A Step-by-Step Guide to Unlocking Insights from Your Data

Customizing ggbiplot with GeomBag Function in R for Visualizing High-Dimensional Data

Linear Discriminant Analysis with Morphological Data: A Custom Approach Using R and geomorph Packages

Understanding and Visualizing Stock Market Absorption Ratio over Time Using R Code

Understanding Negative Weights in Principal Component Analysis for Index Construction

Creating Overlapping PCA Plots with Multiple Variables and Custom Colors in R Using prcomp and FactoExtra

Resolving 'names' Attribute Errors When Plotting PCA Results with ggplot2