ariable x has a uniform distribution with values between 5 and 15 being equally likely. Variable y has a Pareto distribution. A Gaussian copula is used to define the correlation between the two distributions. A Gaussian copula is used to define the correlation between the two distributions. The Pareto distribution for variable y has a probability density function aca/ya +1 for values of y between c and infinity where c = 4 and a = 0.5. Produce a table similar to Table 9.5

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Variable x has a uniform distribution with values between 5 and 15 being equally likely. Variable y has a Pareto distribution. A Gaussian copula is used to define the correlation between the two distributions. A Gaussian copula is used to define the correlation between the two distributions. The Pareto distribution for variable y has a probability density function aca/ya +1 for values of y between c and infinity where c = 4 and a = 0.5. Produce a table similar to Table 9.5 in the text considering values of x equal to 7, 9, 11, and 13 and values of y equal to 5, 10, 30, and 60. Assume a copula correlation of 0.4.

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