Package index

Core Hypothesis Testing

Main testing functions and formula/model interfaces

lmdt_test()

Local Manifold Dispersion Test for Heteroskedasticity

S3 Diagnostics and Visualizations

Methods for displaying and plotting test outcomes

print(<lmdt>) summary(<lmdt>)

Methods for LMDT Test Results

plot(<lmdt>)

Plot Diagnostic Visualizations for LMDT

Spectral Graph Infrastructure

Graph Laplacian and self-tuning affinity matrices

lmdt_graph()

Self-Tuning Manifold Graph Construction

High-Dimensional Denoising

Singular-value thresholding and metric learning for p > 50

lmdt_pca()

Gavish–Donoho Optimal Adaptive PCA Denoising

lmdt_metric()

Supervised Metric Learning for Sparse Noise Dilution

Package Overview

Documentation and citation information

LMDT-package LMDT

Local Manifold Dispersion Test for Heteroskedasticity