Tutorial on principal component analysis, with applications in R

TL;DR

This tutorial explains how to perform principal component analysis in R, demonstrating the steps and computations involved in reducing data dimensionality through dominant principal components.

Contribution

It provides a practical, step-by-step tutorial on PCA implementation in R, including computations and applications.

Findings

Clear demonstration of PCA steps in R

Guidance on selecting principal components

Application examples in data reduction

Abstract

This tutorial reviews the main steps of the principal component analysis of a multivariate data set and its subsequent dimensional reduction on the grounds of identified dominant principal components. The underlying computations are demonstrated and performed by means of a script written in the statistical software package R.