Package: copula
Version: 0.9-9
Date: 2011-12-01
Title: Multivariate dependence with copulas
Author: Jun Yan <jun.yan@uconn.edu> and Ivan Kojadinovic
<ivan.kojadinovic@univ-pau.fr>
Maintainer: Ivan Kojadinovic <ivan.kojadinovic@univ-pau.fr>
Depends: R (>= 2.14), methods, mvtnorm, scatterplot3d, pspline
Enhances: nor1mix
Description: Classes (S4) of commonly used copulas including elliptical
(normal and t), Archimedean (Clayton, Gumbel, Frank, and
Ali-Mikhail-Haq), extreme value (Gumbel, Husler-Reiss,
Galambos, Tawn, and t-EV), and other families (Plackett and
Farlie-Gumbel-Morgenstern). Methods for density, distribution,
random number generation, bivariate dependence measures,
perspective and contour plots. Functions for fitting copula
models with variance estimate. Independence tests among random
variables and random vectors. Serial independence tests for
univariate and multivariate continuous time series.
Goodness-of-fit tests for copulas based on multipliers and on
the parametric bootstrap. Bivariate and multivariate tests of
extreme-value dependence. Bivariate tests of exchangeability.
License: GPL (>= 3)
Collate: Classes.R Copula.R derCdfPdf.R E.R amhCopula.R amhExpr.R
archmCopula.R asymCopula.R asymExplicitCopula.R claytonCopula.R
claytonExpr.R debye.R ellipCopula.R evCopula.R evTests.R
exchTests.R fgmCopula.R fitCopula.R fitMvdc.R frankCopula.R
frankExpr.R galambosCopula.R galambosExpr-math.R galambosExpr.R
gofEVTests.R gofTests.R graphics.R gumbelCopula.R gumbelExpr.R
huslerReissCopula.R huslerReissExpr.R indepCopula.R
indepTests.R logseries.R mult.R mvdc.R normalCopula.R
plackettCopula.R plackettExpr.R schlatherCopula.R stable.R
tCopula.R tawnCopula.R tawnExpr.R tevCopula.R zzz.R
Repository: CRAN
Packaged: 2011-12-01 12:28:08 UTC; ikojadin
Date/Publication: 2011-12-02 16:22:52

Description: Classes (S4) of commonly used elliptical, Archimedean,
extreme value and some more copula families.  Methods for
density, distribution, random number generation, bivariate
dependence measures, perspective and contour plots.  Fitting
copula models including variance estimates.  Independence and
serial (univariate and multivariate) independence tests, and
other copula related tests.  Goodness-of-fit tests for copulas
based on multipliers, the parametric bootstrap with several
transformation options.  Merged former package 'nacopula' for
nested Archimedean copulas: Efficient sampling algorithms,
various estimators, goodness-of-fit tests and related tools and