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英文文献：A Simplified, General Approach to Simulating from Multivariate Copula Functions-一种简化的、通用的多元联结函数模拟方法
英文文献作者：Goodwin, Barry K.
英文文献摘要：
Copulas have become an important analytic tool for characterizing multivariate distributions and dependence. One is often interested in simulating data from copula estimates. The process can be analytically and computationally complex and usually involves steps that are unique to a given parametric copula. We describe an alternative approach that uses \probability{proportional{to{size" (PPS) random sampling with weights formed from the copula likelihood function. The method is flexible and can be applied to parametric and nonparametric marginal density estimates. The precision of the simulation can be calibrated by adjusting the density of the multidimensional grid used in the simulation process. The approach is fully transparent to any copula function with continuous random variables. An example evaluates a number of goodness-of-fit criteria and provides strong support for the validity and practicality of the method.
Copulas已成为表征多变量分布和相关性的重要分析工具。人们通常对通过联结估计来模拟数据感兴趣。这个过程在分析和计算上可以是复杂的，通常涉及到的步骤是唯一的给定参数连接。我们描述了一种使用概率与大小成比例(PPS)随机抽样的替代方法，其权值由copula似然函数形成。该方法灵活，可用于参数和非参数边缘密度估计。通过调整模拟过程中多维网格的密度，可以实现模拟精度的校准。该方法对任意具有连续随机变量的联结函数都是完全透明的。通过算例对多个拟合优度准则进行了评价，为该方法的有效性和实用性提供了有力的支持。
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