Purpose
Input various Marginals and view Gaussian Copula .Load the libraries

> library(scatterplot3d)
> library(copula)

Create a Gaussian Copula with t Marginals with rho as 0.2 and 0.9

> par(mfrow = c(2, 2))
> gaus.cop <- ellipCopula(family = "normal", dim = 2, dispstr = "ex",
+     param = 0.2)
> gaus.mvdc <- mvdc(copula = gaus.cop, margins = c("norm", "norm"),
+     paramMargins = list(list(mean = 0, sd = 1), list(mean = 0,
+         sd = 1)))
> contour(gaus.mvdc, dmvdc, xlim = c(-3, 3), ylim = c(-3, 3), main = paste("Marginal gaussian (rho) = ",
+     0.2))
> gaus.cop <- ellipCopula(family = "normal", dim = 2, dispstr = "ex",
+     param = 0.9)
> gaus.mvdc <- mvdc(copula = gaus.cop, margins = c("norm", "norm"),
+     paramMargins = list(list(mean = 0, sd = 1), list(mean = 0,
+         sd = 1)))
> contour(gaus.mvdc, dmvdc, xlim = c(-3, 3), ylim = c(-3, 3), main = paste("Marginal gaussian (rho) = ",
+     0.9))
> t.cop <- ellipCopula(family = "normal", dim = 2, dispstr = "ex",
+     param = 0.2)
> t.mvdc <- mvdc(copula = t.cop, margins = c("t", "t"), paramMargins = list(list(df = 3),
+     list(df = 3)))
> contour(t.mvdc, dmvdc, xlim = c(-3, 3), ylim = c(-3, 3), main = paste("Marginal t (rho) = ",
+     0.2))
> t.cop <- ellipCopula(family = "normal", dim = 2, dispstr = "ex",
+     param = 0.9)
> t.mvdc <- mvdc(copula = t.cop, margins = c("t", "t"), paramMargins = list(list(df = 3),
+     list(df = 3)))
> contour(t.mvdc, dmvdc, xlim = c(-3, 3), ylim = c(-3, 3), main = paste("Marginal t (rho) = ",
+     0.9))

GaussianCopula-002.jpg