FDR, covariance matrix estimation, and graphical models in high dimensions · Advanced treatise

Introduction

What this guide covers

Introduction Treatise on Multivariate Statistical Inference

Overview

Topics covered

• Introduction
• False Discovery Rate, Covariance and High-Dimensional Graphical Models
• The Curse of Dimensionality and Spectral Collapse
• Estimation of covariance matrices by thresholding (Thresholding)
• Spectral and spatial shrinkage methods
• Nonlinear contraction of eigenvalues

Related concepts

Main connections

• Linear algebra & matrices
• Multiple testing & FWER/FDR
• Regularization (Lasso / Ridge / Elastic Net)
• Variance & standard deviation
• Normal (Gaussian) distribution
• Hypothesis testing

Compatible notation

Mathematical sample in LaTeX

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