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
CRAN checks:	fgac results

Documentation:

Reference manual:

fgac.pdf

Downloads:

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
macOS binaries:	r-release (arm64): fgac_0.6-1.tgz, r-oldrel (arm64): fgac_0.6-1.tgz, r-release (x86_64): fgac_0.6-1.tgz, r-oldrel (x86_64): fgac_0.6-1.tgz
Old sources:	fgac archive

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