Non-parametric Methods

12.

Advanced Topics and Extensions

12.1.

Asymptotic Theory

12.1.1.

Asymptotic Relative Efficiency

12.1.1.1.

Pitman Efficiency

12.1.1.2.

Bahadur Efficiency

12.1.2.

Large Sample Properties

12.1.2.1.

12.1.2.2.

Asymptotic Normality

12.1.3.

Contiguity Theory

12.1.3.1.

Local Alternatives

12.1.3.2.

12.2.

Robust Statistics Connection

12.2.1.

12.2.2.

Breakdown Point

12.2.3.

Influence Functions

12.3.

Modern Developments

12.3.1.

High-Dimensional Methods

12.3.1.1.

12.3.1.2.

12.3.2.

Machine Learning Connections

12.3.2.1.

Tree-Based Methods

12.3.2.2.

Ensemble Methods

12.3.3.

Bayesian Non-parametrics

12.3.3.1.

Dirichlet Processes

12.3.3.2.

Gaussian Processes

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11. Practical Implementation

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1. Introduction to Non-parametric Statistics