Package: LMDT
Type: Package
Title: Local Manifold Dispersion Test for Heteroskedasticity
Version: 0.1.0
Authors@R: person(given = "Ahmed Sattar",
                  family = "Jabbar",
                  role = c("aut", "cre"),
                  email = "ahmed.state.me@gmail.com")
Description: 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.
License: GPL (>= 3)
URL: https://amjed-droid.github.io/LMDT/,
        https://github.com/amjed-droid/LMDT
BugReports: https://github.com/amjed-droid/LMDT/issues
Depends: R (>= 4.0.0)
Imports: stats
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.3.1
NeedsCompilation: no
Packaged: 2026-10-14 23:29:15 UTC; intel
Author: Ahmed Sattar Jabbar [aut, cre]
Maintainer: Ahmed Sattar Jabbar <ahmed.state.me@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 09:30:02 UTC
