Introduction
What this guide covers
Introduction Introduction Advanced Multivariate Analysis · Probability Theory
Overview
Topics covered
- Introduction
- The Multivariate Normal Distribution
- Introduction and fundamentals of random vectors
- Algebraic Properties of the Positive Definite Covariance Matrix
- The multivariate normal density
- Derivation of General Density by Change of Variable
Related concepts
Main connections
Compatible notation
Mathematical sample in LaTeX
The expression is rendered accessibly, with its LaTeX source preserved below.
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\boldsymbol{\mu} = \E[\mathbf{X}] = \big( \E[X_1], \E[X_2], \dots, \E[X_p] \big)^T.