Stochastic simulation: Applications in inference and optimization

Introduction

What this guide covers

Introduction simulate |> generate_pseudorandom_() |> estimate_integrals () |> optimize_function () Introduction Computational Statistics · Expert Level

Overview

Topics covered

• Introduction
• Stochastic Simulation in Inference and Optimization
• Stochastic Fundamentals of Simulation
• Pseudorandom Number Generation
• The Inverse Transformation Theorem
• Monte Carlo Integration and Variance Reduction Methods

Related concepts

Main connections

• Monte Carlo simulation
• Variance & standard deviation
• Markov chain Monte Carlo (MCMC)
• Bootstrap resampling
• Survey sampling methods
• Calculus & differentiation

Compatible notation

Mathematical sample in LaTeX

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