fgac: Generalized Archimedean Copula

Bi-variate data fitting is done by two stochastic components: the marginal distributions and the dependency structure. The dependency structure is modeled through a copula. An algorithm was implemented considering seven families of copulas (Generalized Archimedean Copulas), the best fitting can be obtained looking all copula's options (totally positive of order 2 and stochastically increasing models).

Version: 0.6-1
Published: 2012-10-29
Author: Veronica Andrea Gonzalez-Lopez
Maintainer: Veronica Andrea Gonzalez-Lopez <veronica at ime.unicamp.br>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
Materials: README
In views: Distributions, Finance, Multivariate
CRAN checks: fgac results


Reference manual: fgac.pdf
Package source: fgac_0.6-1.tar.gz
Windows binaries: r-devel: fgac_0.6-1.zip, r-release: fgac_0.6-1.zip, r-oldrel: fgac_0.6-1.zip
OS X Mavericks binaries: r-release: fgac_0.6-1.tgz, r-oldrel: fgac_0.6-1.tgz
Old sources: fgac archive