NO.PZ2018122701000058
问题如下：
Which of the following statements about correlation and copula are correct?
I.Copula enables the structures of correlation between variables to be calculated separately from their marginal distributions.
II.Transformation of variables does not change their correlation structure.
III.Correlation can be a useful measure of the relationship between variables drawn from a distribution without a defined variance.
IV.Correlation s a good measure of dependence when the measured variables are distributed as multivariate elliptical.
选项：
A.I and IV only
B.II, III, and IV only
C.I and III only
D.II and IV only
解释：
A is correct.
考点Copula Functions
解析
"I" is true. Using the copula approach, we can calculate the structures of correlation between variables separately from the marginal distributions. "IV" is also true. Correlation is a good measure of dependence when the measured variables are distributed as multivariate elliptical.
"II" is false. The correlation between transformed variables will not always be the same as the correlation between those same variables before transformation. Data transformation can sometimes alter the correlation estimate. "III" is also false. Correlation is not defined unless variances are finite.
I和III不是很明白，
ICopula enables the structures of correlation between variables to be calculated separately from their marginal distributions.是翻译成“Copula根据变量的边缘分布分别计算变量之间的相关性的结构”吗？这个具体的逻辑没太明白，变量的边缘分布，是指高斯copula中的G1（u1）吗
III.Correlation can be a useful measure of the relationship between variables drawn from a distribution without a defined variance.
这里的drawn from a distribution without a defined variance.请问指的是什么？
谢谢！
