Statistical Modeling & Regression · Multivariate Analysis

Multivariate analysis · Dimensionality reduction - PCA

Public introduction · full guide in Eikos

Introduction

What this guide covers

Introduction Chart from the original guide

Overview

Topics covered

  • Introduction
  • Principal Component Analysis (PCA)
  • The Curse of Dimensionality and Spatial Reduction
  • Rigorous Mathematical Formulation of the ACP
  • Projected Variance Maximization
  • Successive Main Components

Related concepts

Main connections

  • Linear algebra & matrices
  • Variance & standard deviation
  • Principal component analysis (PCA)
  • Calculus & differentiation
  • Outliers & influence diagnostics
  • Maximum likelihood estimation

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

limp→∞Dmax−DminDmin=0
View LaTeX source\lim_{p \to \infty} \frac{D_{\max} - D_{\min}}{D_{\min}} = 0