Simulation and resampling — Theoretical and practical treatise

Introduction

What this guide covers

A rigorous study on computational mechanisms for inference, approximation of probability measures and non-parametric statistical validation.

Overview

Topics covered

• Introduction
• Simulation and Resampling
• Introduction and Fundamentals of Simulation
• Generation of Random Variables and Pseudorandom Numbers
• The Inverse Transform Method
• The Acceptance-Rejection Method

Related concepts

Main connections

• Bootstrap resampling
• Variance & standard deviation
• Markov chain Monte Carlo (MCMC)
• Calculus & differentiation
• Quantiles & percentiles
• Bayes' theorem & priors

Compatible notation

Mathematical sample in LaTeX

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