How to fit a copula model in R [heavily revised]. Part 2: fitting the copula. Full article at

copulas_revised_2_1.R

# Estimate x  gamma distribution parameters and visually compare simulated vs observed data
x_mean <- mean(mydata$x)
x_var <- var(mydata$x)
x_rate <- x_mean / x_var
x_shape <- ( (x_mean)^2 ) / x_var

hist(mydata$x, breaks = 20, col = "green", density = 20)
hist(rgamma( nrow(mydata), rate = x_rate, shape = x_shape), breaks = 20,col = "blue", add = T, density = 20, angle = -45)

# Estimate y gamma distribution parameters and visually compare simulated vs observed data
y_mean <- mean(mydata$y)
y_var <- var(mydata$y)
y_rate <- y_mean / y_var
y_shape <- ( (y_mean)^2 ) / y_var
hist(mydata$y, breaks = 20, col = "green", density = 20)
hist(rgamma(nrow(mydata), rate = y_rate, shape = y_shape), breaks = 20, col = "blue", add = T, density = 20, angle = -45)