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 |
| macOS binaries: | r-release: fgac_0.6-1.tgz, r-oldrel: fgac_0.6-1.tgz |
| Old sources: | fgac archive |
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