R语言 VineCopula包 RVineMatrix()函数中文帮助文档(中英文对照)

loveR · 发表于 2012-10-1 16:11:49

RVineMatrix(VineCopula)
RVineMatrix()所属R语言包：VineCopula

 R-vine copula model in matrix notation
 在矩阵符号R-藤copula模型

 译者：生物统计家园网机器人LoveR

描述----------Description----------

This function creates an RVineMatrix object which encodes an R-vine copula model. It contains the matrix identifying the R-vine tree structure, the matrix identifying the copula families utilized and two matrices for corresponding parameter values.
这个函数创建一个RVineMatrix对象编码R-葡萄树的copula模型。它包含了矩阵确定R-葡萄树的结构，矩阵识别利用Copula函数的家庭和两个矩阵对应的参数值。

用法----------Usage----------

RVineMatrix(Matrix, family=array(0,dim=dim(Matrix)),
 par=array(NA,dim=dim(Matrix)),
 par2=array(NA,dim=dim(Matrix)), names=NULL)

参数----------Arguments----------

参数：Matrix
Lower triangular d x d matrix that defines the R-vine tree structure.
下三角的DXD矩阵，定义的R-葡萄树的树结构。

参数：family
Lower triangular d x d matrix with zero diagonal entries that assigns the pair-copula families to each (conditional) pair defined by Matrix (default: family = array(0,dim=dim(Matrix))). The bivariate copula families are defined as follows: 0 = independence copula 1 = Gaussian copula 2 = Student t copula (t-copula) 3 = Clayton copula 4 = Gumbel copula 5 = Frank copula 6 = Joe copula 7 = BB1 copula 8 = BB6 copula 9 = BB7 copula 10 = BB8 copula 13 = rotated Clayton copula (180 degrees; “survival Clayton”) 14 = rotated Gumbel copula (180 degrees; “survival Gumbel”) 16 = rotated Joe copula (180 degrees; “survival Joe”) 17 = rotated BB1 copula (180 degrees; “survival BB1”) 18 = rotated BB6 copula (180 degrees; “survival BB6”) 19 = rotated BB7 copula (180 degrees; “survival BB7”) 20 = rotated BB8 copula (180 degrees; “survival BB8”) 23 = rotated Clayton copula (90 degrees) 24 = rotated Gumbel copula (90 degrees) 26 = rotated Joe copula (90 degrees) 27 = rotated BB1 copula (90 degrees) 28 = rotated BB6 copula (90 degrees) 29 = rotated BB7 copula (90 degrees) 30 = rotated BB8 copula (90 degrees) 33 = rotated Clayton copula (270 degrees) 34 = rotated Gumbel copula (270 degrees) 36 = rotated Joe copula (270 degrees) 37 = rotated BB1 copula (270 degrees) 38 = rotated BB6 copula (270 degrees) 39 = rotated BB7 copula (270 degrees) 40 = rotated BB8 copula (270 degrees)
下三角DXD矩阵与零对角线条目的对Copula的家庭，分配到每个（有条件的）对Matrix（默认定义：family = array(0,dim=dim(Matrix))）。二元Copula的家庭被定义为如下： 0独立系词参考1=高斯系词参考的2学生t Copula函数（T-Copula函数）< >3=克莱顿系词参考4= Gumbel分布Copula的参考5=弗兰克·系词参考6=乔系词参考7 = BB1 Copula的参考8= BB6 Copula的参考9= BB7系词参考10 = BB8系词参考13=旋转克莱顿系词（180度“生存克莱顿”）参考14=旋转（180度“生存冈贝尔”）Gumbel分布Copula的参考16=旋转（180度“生存乔”乔系词;)参考17=旋转（180度;“BB1生存”）BB1 Copula的参考18=旋转BB6 Copula函数（180度“生存BB6”的）参考19=旋转BB7系词（180度“生存BB7”）参考20=旋转BB8系词（180度“生存BB8”）参考23=旋转克莱顿系词（90度）参考24=系词（90度）旋转冈贝尔参考26=旋转乔系词（90度）参考27=旋转BB1 Copula函数（90度）参考28=旋转BB6 Copula函数（90度）参考29=旋转BB7系词（90度）参考30=旋转BB8系词（90度）参考33=系词（270度）旋转克莱顿参考34=旋转（270度）Gumbel分布Copula的参考36=旋转乔系词（270度）参考37=旋转BB1 Copula函数（270度）参考38=旋转BB6 Copula函数（270度）参考39=旋转BB7系词（270度） >40=旋转BB8系词（270度）

参数：par
Lower triangular d x d matrix with zero diagonal entries that assigns the (first) pair-copula parameter to each (conditional) pair defined by Matrix (default: par = array(NA,dim=dim(Matrix))).
DXD下三角矩阵，零对角元素分配（第一）对Copula函数的参数，每个（有条件的）对定义的Matrix的 （默认：par = array(NA,dim=dim(Matrix))“）。

参数：par2
Lower triangular d x d matrix with zero diagonal entries that assigns the second parameter for pair-copula families with two parameters to each (conditional) pair defined by Matrix (default: par2 = array(NA,dim=dim(Matrix))).
下三角DXD矩阵的零对角元素分配的第二个参数对Copula的家庭的两个参数来定义的每个（有条件的）对Matrix（默认：par2 = array(NA,dim=dim(Matrix))）。

参数：names
A vector of names for the d variables; default: names = NULL.
一个向量D变量的名称;默认：names = NULL。

值----------Value----------

An RVineMatrix object with the following matrix components:
RVineMatrix对象与下面的矩阵组成部分：

参数：Matrix
R-vine tree structure matrix.
R-葡萄树结构矩阵。

参数：family
Pair-copula family matrix with values as above.
对Copula的家庭矩阵值以上。

参数：par
Pair-copula parameter matrix.
对Copula函数的参数矩阵。

参数：par2
Second pair-copula parameter matrix with parameters necessary for pair-copula families with two parameters.
第二对Copula函数的参数矩阵所必需对Copula的家庭，有两个参数与参数。

（作者）----------Author(s)----------

Jeffrey Dissmann

参考文献----------References----------

Selecting and estimating regular vine copulae and application to financial returns. Submitted for publication. http://mediatum.ub.tum.de/node?id=1079277

参见----------See Also----------

RVineMLE, RVineSim, C2RVine, D2RVine, R2CVine, R2DVine
RVineMLE，RVineSim，C2RVine，D2RVine，R2CVine，R2DVine

实例----------Examples----------

# define 5-dimensional R-vine tree structure matrix[定义5维的R-葡萄树结构矩阵]
Matrix = c(5,2,3,1,4,0,2,3,4,1,0,0,3,4,1,0,0,0,4,1,0,0,0,0,1)
Matrix = matrix(Matrix,5,5)

# define R-vine pair-copula family matrix[定义R-藤对Copula的家庭矩阵]
family = c(0,1,3,4,4,0,0,3,4,1,0,0,0,4,1,0,0,0,0,3,0,0,0,0,0)
family = matrix(family,5,5)

# define R-vine pair-copula parameter matrix[定义R-藤对Copula函数的参数矩阵]
par = c(0,0.2,0.9,1.5,3.9,0,0,1.1,1.6,0.9,0,0,0,1.9,0.5,
 0,0,0,0,4.8,0,0,0,0,0)
par = matrix(par,5,5)

# define second R-vine pair-copula parameter matrix[定义第二个R-藤对Copula函数的参数矩阵]
par2 = matrix(0,5,5)

# define RVineMatrix object[定义RVineMatrix对象]
RVM = RVineMatrix(Matrix=Matrix,family=family,par=par,par2=par2,
 names=c("V1","V2","V3","V4","V5"))

转载请注明:出自生物统计家园网(http://www.biostatistic.net)。

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