Statistical computing: Resampling methods and non-parametric inference theory · Introduction

Introduction

What this guide covers

An analytical treatise on Jackknife theory, Bootstrap paradigms, permutation testing and cross-validation from the perspective of asymptotic and non-parametric inference.

Overview

Topics covered

Introduction
Computer-Based Inference: Rigorous Theory and Resampling Methods
Non-Parametric Inference and the Substitution Principle
The Substitution Principle (Plug-in Principle)
The Jackknife Method (Quenouille-Tukey)
Bias Estimation using Jackknife

Related concepts

Main connections

Compatible notation

Mathematical sample in LaTeX

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

\hat{F}_n(x) = \frac{1}{n} \sum_{i=1}^{n} \mathbb{I}(X_i \leq x)

View LaTeX source

\hat{F}_n(x) = \frac{1}{n} \sum_{i=1}^{n} \mathbb{I}(X_i \leq x)