Statistical Modeling & Regression · Bayesian Statistics

Bayesian computation methods · Treatise on modern inference

Public introduction · full guide in Eikos

Introduction

What this guide covers

Introduction Introduction Advanced Statistical Computing · Technical Monograph

Overview

Topics covered

  • Introduction
  • Bayesian Computation
  • Bayesian Inference and Analytical Intractability
  • The Root of Analytical Intractability
  • Classical Numerical Integration and Quadrature
  • Gauss-Hermite Quadrature

Related concepts

Main connections

  • Bayes' theorem & priors
  • Markov chain Monte Carlo (MCMC)
  • Monte Carlo simulation
  • Maximum likelihood estimation
  • Calculus & differentiation
  • Variance & standard deviation

Compatible notation

Mathematical sample in LaTeX

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

p(𝛉∣𝐲)=p(𝐲∣𝛉)p(𝛉)p(𝐲)
View LaTeX sourcep(\boldsymbol{\theta} \mid \mathbf{y}) = \frac{p(\mathbf{y} \mid \boldsymbol{\theta}) \, p(\boldsymbol{\theta})}{p(\mathbf{y})}