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: 1.3.3
Depends: R (≥ 2.10), GrassmannOptim, Matrix
Published: 2014-10-29
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.jstatsoft.org/v61/i03/
NeedsCompilation: no
Citation: ldr citation info
CRAN checks: ldr results


Reference manual: ldr.pdf
Package source: ldr_1.3.3.tar.gz
Windows binaries: r-devel: ldr_1.3.3.zip, r-release: ldr_1.3.3.zip, r-oldrel: ldr_1.3.3.zip
OS X El Capitan binaries: r-release: ldr_1.3.3.tgz
OS X Mavericks binaries: r-oldrel: ldr_1.3.3.tgz
Old sources: ldr archive

Reverse dependencies:

Reverse suggests: BCEA


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