Local Manifold Dispersion Test for Heteroskedasticity R package LMDT version 0.1.0 Implements the Local Manifold Dispersion Test (LMDT) for detecting complex, non-linear, and high-dimensional heteroskedasticity in linear regression models. LMDT measures the spectral smoothness (Dirichlet energy) of robust log-dispersion residuals over a self-tuning k-nearest neighbors graph Laplacian, as formulated in Jabbar (2026). The test statistic is asymptotically distribution-free with respect to error kurtosis and accommodates high-dimensional covariates (p > 50) via Gavish-Donoho optimal hard thresholding and supervised metric learning. Software Depends: R (>= 4.0.0) Imports: stats Suggests: testthat (>= 3.0.0), knitr, rmarkdown Ahmed Sattar Jabbar <ahmed.state.me@gmail.com> Comprehensive R Archive Network (CRAN) Ahmed Sattar Jabbar [aut, cre] GPL (>= 3) 2026-10-24 application/tgz https://CRAN.R-project.org/package=LMDT doi:10.32614/CRAN.package.LMDT