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vine copular

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Package VineCopulaFebruary 15, 2013Type PackageTitle Statistical inference of vine copulasVersion 1.1-1Date 2013-02-07Author Ulf Schepsmeier, Jakob Stoeber, Eike Christian BrechmannMaintainer Ulf Schepsmeier Depends R (>= 2.11.0), MASS, mvtnorm, igraph0Suggests CDVine, TSPDescription This package provides functions for statistical inferenceof vine copulas. It contains tools for bivariate exploratorydata analysis, bivariate copula selection and (vine) treeconstruction. Models can be estimated either sequentially or byjoint maximum likelihood estimation. Sampling algorithms andplotting methods are also included. Data is assumed to lie inthe unit hypercube (so-called copula data). For C- and D-vineslinks to the package CDVine are provided.License GPL (>= 2)LazyLoad yesRepository CRANDate/Publication 2013-02-07 17:24:28NeedsCompilation yes12 R topics documented:R topics documented:VineCopula-package . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3BiCopCDF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5BiCopChiPlot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7BiCopDeriv . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9BiCopDeriv2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11BiCopEst . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12BiCopGofTest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15BiCopHfunc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18BiCopHfuncDeriv . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20BiCopHfuncDeriv2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22BiCopIndTest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23BiCopKPlot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25BiCopLambda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26BiCopMetaContour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29BiCopName . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32BiCopPar2TailDep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33BiCopPar2Tau . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36BiCopPDF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38BiCopSelect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40BiCopSim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43BiCopTau2Par . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44BiCopVuongClarke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46C2RVine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48D2RVine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50daxreturns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52RVineAIC/BIC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53RVineClarkeTest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54RVineCopSelect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56RVineGrad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59RVineHessian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61RVineLogLik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63RVineMatrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65RVineMLE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68RVinePar2Tau . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70RVineSeqEst . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71RVineSim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73RVineStdError . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74RVineStructureSelect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76RVineTreePlot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79RVineVuongTest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81TauMatrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83Index 85VineCopula-package 3VineCopula-package Statistical inference of vine copulasDescriptionThis package provides functions for statistical inference of vine copulas. It contains tools for bivari-ate exploratory data analysis, bivariate copula selection and (vine) tree construction. Models can beestimated either sequentially or by joint maximum likelihood estimation. Sampling algorithms andplotting methods are also included. Data is assumed to lie in the unit hypercube (so-called copuladata). For C- and D-vines links to the package CDVine are provided.DetailsPackage: VineCopulaType: PackageVersion: 1.1-1Date: 2013-02-07License: GPL (>=2)Depends: R ( 2.11.0), MASS, mvtnorm, igraph0Suggests: CDVine, TSPLazyLoad: yesRemarkThe package VineCopula is a continuation of the package CDVine by U. Schepsmeier and E. C.Brechmann (see Brechmann and Schepsmeier (2013)). It includes all functions implemented inCDVine for the bivariate case (BiCop-functions).Bivariate copula familiesIn this package several bivariate copula families are included for bivariate analysis as well asfor multivariate analysis using vine copulas. It provides functionality of elliptical (Gaussian andStudent-t) as well as Archimedean (Clayton, Gumbel, Frank, Joe, BB1, BB6, BB7 and BB8) cop-ulas to cover a large bandwidth of possible dependence structures. For the Archimedean copulafamilies rotated versions are included to cover negative dependence too. The two parameter BB1,BB6, BB7 and BB8 copulas are however numerically instable for large parameters, in particular,if BB6, BB7 and BB8 copulas are close to the Joe copula which is a boundary case of these threecopula families. In general, the user should be careful with extreme parameter choices.The following table shows the parameter ranges of bivariate copula families with parameters pa

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