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).
|Author:||Veronica Andrea Gonzalez-Lopez|
|Maintainer:||Veronica Andrea Gonzalez-Lopez <veronica at ime.unicamp.br>|
|License:||GPL-2 | GPL-3 [expanded from: GPL]|
|In views:||Distributions, Finance, Multivariate|
|CRAN checks:||fgac results|
|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|
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