Description: This package estimates factor analysis models using a
genetic algorithm, which permits a general mechanism for
restricted optimization with arbitrary restrictions that are
chosen at run time with the help of a GUI. Importantly,
inequality restrictions can be imposed on functions of multiple
parameters, which provides a new avenues for testing and
generating theories with factor analysis models. This package
also includes an entirely new estimator of the common factor
analysis model called semi-exploratory factor analysis, which
is a general alternative to exploratory and confirmatory factor
analysis. Finally, this package integrates a lot of other
packages that estimate sample covariance matrices and thus
provides a lot of alternatives to the traditional sample
covariance calculation. Note that you need to have the Gtk run
time library installed on your system to use this package; see
the URL below for detailed installation instructions. Most
users would only need to understand the first twenty-four pages
Depends: R (>= 2.7.0), methods, rgenoud (>= 5.4-7), gWidgetsRGtk2 (>=
Suggests: corpcor, mvnmle, polycor, nFactors, Rgraphviz, mvnormtest,

Package: FAiR
Type: Package
Title: Factor Analysis in R
Version: 0.4-14
Date: 2013-08-29
Author: Ben Goodrich
Maintainer: Ben Goodrich <bgokgm@gmail.com>
Description: This package estimates factor analysis models using a
genetic algorithm, which permits a general mechanism for
restricted optimization with arbitrary restrictions that are
chosen at run time with the help of a GUI. Importantly,
inequality restrictions can be imposed on functions of multiple
parameters, which provides a new avenues for testing and
generating theories with factor analysis models. This package
also includes an entirely new estimator of the common factor
analysis model called semi-exploratory factor analysis, which
is a general alternative to exploratory and confirmatory factor
analysis. Finally, this package integrates a lot of other
packages that estimate sample covariance matrices and thus
provides a lot of alternatives to the traditional sample
covariance calculation. Note that you need to have the Gtk run
time library installed on your system to use this package; see
the URL below for detailed installation instructions. Most
users would only need to understand the first twenty-four pages
of the PDF manual.
URL: http://wiki.r-project.org/rwiki/doku.php?id=packages:cran:fair
License: AGPL (>= 3) + file LICENSE
Encoding: UTF-8
Depends: R (>= 2.7.0), methods, rgenoud (>= 5.4-7), gWidgetsRGtk2 (>=
0.0-31), stats4, rrcov, Matrix
Suggests: corpcor, mvnmle, polycor, nFactors, Rgraphviz, mvnormtest,
energy, GPArotation, sem, MASS, psych
LazyLoad: yes
Packaged: 2013-08-30 05:40:48 UTC; goodrich
Repository: CRAN
Date/Publication: 2013-08-30 19:25:59
NeedsCompilation: yes