ldr: Methods for likelihood-based dimension reduction in regression

Functions, methods, and data sets for fitting likelihood-based dimension reduction in regression, using principal fitted components (pfc), likelihood acquired directions (lad), covariance reducing models (core).

Version: 1.3.2
Depends: R (≥ 3.0.0), GrassmannOptim, Matrix
Published: 2014-06-27
Author: Kofi Placid Adragni, Andrew Raim
Maintainer: Kofi Placid Adragni <kofi at umbc.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.math.umbc.edu/~kofi/ldr
NeedsCompilation: no
Citation: ldr citation info
CRAN checks: ldr results

Downloads:

Reference manual: ldr.pdf
Package source: ldr_1.3.2.tar.gz
Windows binaries: r-devel: ldr_1.3.2.zip, r-release: ldr_1.3.2.zip, r-oldrel: ldr_1.3.2.zip
OS X Snow Leopard binaries: r-release: ldr_1.3.2.tgz, r-oldrel: ldr_1.3.2.tgz
OS X Mavericks binaries: r-release: ldr_1.3.2.tgz
Old sources: ldr archive