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
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

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