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hierSDR: Hierarchical Sufficient Dimension Reduction

Provides semiparametric sufficient dimension reduction for central mean subspaces for heterogeneous data defined by combinations of binary factors (such as chronic conditions). Subspaces are estimated to be hierarchically nested to respect the structure of subpopulations with overlapping characteristics. This package is an implementation of the proposed methodology of Huling and Yu (2021) <doi:10.1111/biom.13546>.

Version: 0.1
Depends: R (≥ 3.2.0), MASS, Matrix, locfit, lbfgs
Imports: numDeriv, optimx
Published: 2021-09-23
DOI: 10.32614/CRAN.package.hierSDR
Author: Jared Huling [aut, cre]
Maintainer: Jared Huling <jaredhuling at gmail.com>
BugReports: https://github.com/jaredhuling/hierSDR/issues
License: GPL-2
NeedsCompilation: no
Materials: README
CRAN checks: hierSDR results

Documentation:

Reference manual: hierSDR.pdf

Downloads:

Package source: hierSDR_0.1.tar.gz
Windows binaries: r-devel: hierSDR_0.1.zip, r-release: hierSDR_0.1.zip, r-oldrel: hierSDR_0.1.zip
macOS binaries: r-release (arm64): hierSDR_0.1.tgz, r-oldrel (arm64): hierSDR_0.1.tgz, r-release (x86_64): hierSDR_0.1.tgz, r-oldrel (x86_64): hierSDR_0.1.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.