Package: ssurvdr
Title: Sparse Survival Dimension Reduction for High-Dimensional
        Censored Data
Version: 0.1.0
Authors@R: 
    person("Kabir Opeyemi", "Olorede", , "kabir.olorede@kwasu.edu.ng", role = c("aut", "cre"))
Description: Implements sparse survival sufficient dimension reduction methods
    for high-dimensional censored data, including covariance-stabilised SAVE,
    Maximum Entropy Covariance estimation, information-complexity-guided
    variable weighting, dual-space high-dimensional SAVE computation, row-wise
    post-estimation sparsification paths, and Cox proportional hazards model
    selection.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.1
Depends: R (>= 4.1.0)
Imports: stats, MASS, survival
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
Config/testthat/edition: 3
VignetteBuilder: knitr
URL: https://github.com/ilovemaths/ssurvdr
BugReports: https://github.com/ilovemaths/ssurvdr/issues
NeedsCompilation: no
Packaged: 2026-10-11 19:06:28 UTC; DR OLOREDE
Author: Kabir Opeyemi Olorede [aut, cre]
Maintainer: Kabir Opeyemi Olorede <kabir.olorede@kwasu.edu.ng>
Repository: CRAN
Date/Publication: 2026-10-21 15:50:01 UTC
