RVineStdError(VineCopula)
RVineStdError()所属R语言包：VineCopula
Standard errors of an R-vine copula model
R-藤Copula模型的标准误差
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function calculates the standard errors of a d-dimensional R-vine copula model given the Hessian matrix.
此函数计算一个d维的R-藤copula模型的Hessian矩阵的标准误差。
用法----------Usage----------
RVineStdError(hessian, RVM)
参数----------Arguments----------
参数：hessian
The Hessian matrix of the given R-vine.
的Hessian矩阵R-藤。
参数：RVM
An RVineMatrix object including the structure, the pair-copula families, and the parameters.
RVineMatrix对象包括结构，对Copula的家庭，和参数。
值----------Value----------
参数：se
The calculated standard errors for the first parameter matrix. The entries are ordered with respect to the ordering of the RVM$par matrix.
的第一个参数矩阵的计算标准误差。这些条目进行排序就RVM$par矩阵的顺序。
参数：se2
The calculated standard errors for the second parameter matrix.
计算的标准误差为第二个参数矩阵。
注意----------Note----------
The negative Hessian matrix should be positive semidefinite. Otherwise NAs will be returned in some entries and the non-NA entries may be wrong. If the negaive Hessian matrix is negative definite, then one could try a near positive matrix. The package Matrix provides a function called nearPD to estimate a matrix which is positive definite and close to the given matrix.
应该是负的Hessian矩阵半正定。否则，NAS会自动返回的一些项目和非NA的条目可能是错误的。如果negaive Hessian矩阵是负定的，那么可以尝试接近正矩阵。套件Matrix提供一个函数调用nearPD估计这是正定及接近给定的矩阵的矩阵。
（作者）----------Author(s)----------
Ulf Schepsmeier, Jakob Stoeber
参考文献----------References----------
Derivatives and Fisher information of bivariate copulas. Submitted for publication. http://mediatum.ub.tum.de/node?id=1106541.
Is there significant time-variation in multivariate dependence? In preparation. http://de.arxiv.org/abs/1205.4841.
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----------
BiCopDeriv, BiCopDeriv2, BiCopHfuncDeriv, BiCopHfuncDeriv2, <br>
BiCopDeriv，BiCopDeriv2，BiCopHfuncDeriv，BiCopHfuncDeriv2，参考
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"))
# simulate a sample of size 300 from the R-vine copula model[从R-藤copula模型，模拟样品的尺寸为300]
simdata = RVineSim(300,RVM)
# compute the Hessian matrix of the first row of the data[计算Hessian矩阵的第一行中的数据]
out2 = RVineHessian(simdata,RVM)
# get the standard errors[得到的标准误差]
RVineStdError(out2$hessian,RVM)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
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发表于 2012-10-1 16:12:18
