BiCopDeriv2(VineCopula)
BiCopDeriv2()所属R语言包：VineCopula
Second derivatives of a bivariate copula density
二阶导数的二元Copula的密度
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function evaluates the second derivative of a given parametric bivariate copula density with respect to its parameter(s) and/or its arguments.
此函数计算第二导数的一个给定的参数二元Copula的密度相对于它的参数（s）和/或它的参数。
用法----------Usage----------
BiCopDeriv2(u1, u2, family, par, par2=0, deriv="par")
参数----------Arguments----------
参数：u1,u2
Numeric vectors of equal length with values in [0,1].
数值向量长度相等的值在[0,1]。
参数：family
An integer defining the bivariate copula family: <br> 0 = independence copula <br> 1 = Gaussian copula <br> 2 = Student t copula (t-copula) <br> 3 = Clayton copula <br> 4 = Gumbel copula <br> 5 = Frank copula <br> 6 = Joe copula <br> 13 = rotated Clayton copula (180 degrees; “survival Clayton”) <br> 14 = rotated Gumbel copula (180 degrees; “survival Gumbel”) <br> 16 = rotated Joe copula (180 degrees; “survival Joe”) <br> 23 = rotated Clayton copula (90 degrees) <br> 24 = rotated Gumbel copula (90 degrees) <br> 26 = rotated Joe copula (90 degrees) <br> 33 = rotated Clayton copula (270 degrees) <br> 34 = rotated Gumbel copula (270 degrees) <br> 36 = rotated Joe copula (270 degrees) <br>
一个整数，定义二元Copula的家庭：<BR>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）参考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=旋转乔系词（180度“生存乔”）参考23=旋转克莱顿系词（90度）参考24=旋转冈贝尔系词（90度）参考26=旋转乔系词（90度）参考33=旋转克莱顿系词（270度）参考34=旋转冈贝尔系词（270度）参考36=旋转乔系词（ 270度）参考
参数：par
Copula parameter.
Copula函数的参数。
参数：par2
Second parameter for bivariate t-copula; default: par2 = 0.
二元T-Copula函数的第二个参数为默认：par2 = 0。
参数：deriv
Derivative argument <br> "par" = second derivative with respect to the first parameter (default)<br> "par2" = second derivative with respect to the second parameter (only available for the t-copula) <br> "u1" = second derivative with respect to the first argument u1 <br> "u2" = second derivative with respect to the second argument u2 <br> "par1par2" = second derivative with respect to the first and second parameter (only available for the t-copula) <br> "par1u1" = second derivative with respect to the first parameter and the first argument <br> "par2u1" = second derivative with respect to the second parameter and the first argument (only available for the t-copula) <br> "par1u2" = second derivative with respect to the first parameter and the second argument <br> "par2u2" = second derivative with respect to the second parameter and the second argument (only available for the t-copula) <br>
导数<BR> "par"二阶导数的第一个参数（默认）参考"par2"=二阶导数的t-Copula函数的第二个参数（仅适用）< >"u1"二阶导数的第一个参数u1参考"u2"=二阶导数的第二个参数u2参考"par1par2" =秒衍生物相对于所述第一和第二参数（仅可供叔系词）参考"par1u1"=二阶导数相对于所述第一参数和第一个参数<br>物理化学学报"par2u1"=二阶导数的第二个参数，第一个参数（仅适用于T-Copula的）参考"par1u2"二阶导数的第一个参数，第二个参数<BR>"par2u2"二阶导数的第二个参数，第二个参数（仅适用于T-Copula的）参考
值----------Value----------
A numeric vector of the second bivariate copula derivative with respect to deriv evaluated at u1 and u2 with parameter(s) par and par2.
一个数值向量的第二个二元Copula的衍生物就derivu1评估和u2参数（S）par和par2。
（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.
参见----------See Also----------
RVineGrad, RVineHessian, BiCopDeriv, BiCopHfuncDeriv
RVineGrad，RVineHessian，BiCopDeriv，BiCopHfuncDeriv
实例----------Examples----------
# simulate from a bivariate t-copula[模拟从一个二元T-Copula函数]
simdata = BiCopSim(300,2,-0.7,par2=4)
# second derivative of the bivariate t-copula with respect to the first parameter[相对于第一个参数的二元叔系词的二阶导数]
u1 = simdata[,1]
u2 = simdata[,2]
BiCopDeriv2(u1,u2,2,-0.7,par2=4, deriv="par")
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。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-10-1 16:09:00
