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.
|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|
|Maintainer:||Ben Goodrich <bgokgm at gmail.com>|
|License:||AGPL (≥ 3) + file LICENSE|
|In views:||Multivariate, Psychometrics|
|CRAN checks:||FAiR results|
Factor Analysis in R
|Windows binaries:||r-devel: FAiR_0.4-15.zip, r-release: FAiR_0.4-15.zip, r-oldrel: FAiR_0.4-15.zip|
|OS X Mavericks binaries:||r-release: FAiR_0.4-15.tgz, r-oldrel: FAiR_0.4-15.tgz|
|Old sources:||FAiR archive|
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