conv_funct {ElliptCopulas}R Documentation

Conversion Functions for Elliptical Distributions


An elliptical random vector X of density |det(\Sigma)|^{-1/2} g_d(x' \Sigma^{-1} x) can always be written as X = \mu + R * A * U for some positive random variable R and a random vector U on the d-dimensional sphere. Furthermore, there is a one-to-one mapping between g_d and its one-dimensional marginal g_1.


Convert_gd_To_g1(grid, g_d, d)

Convert_g1_To_Fg1(grid, g_1)

Convert_g1_To_Qg1(grid, g_1)

Convert_g1_To_f1(grid, g_1)

Convert_gd_To_fR2(grid, g_d, d)



the grid on which the values of the functions in parameter are given.


the d-dimensional density generator.


the dimension of the random vector.


the 1-dimensional density generator.


One of the following

See Also

DensityGenerator.normalize to compute the normalized version of a given d-dimensional generator.


grid = seq(0,100,by = 0.01)
g_d = DensityGenerator.normalize(grid = grid, grid_g = 1/(1+grid^3), d = 3)
g_1 = Convert_gd_To_g1(grid = grid, g_d = g_d, d = 3)
Fg_1 = Convert_g1_To_Fg1(grid = grid, g_1 = g_1)
Qg_1 = Convert_g1_To_Qg1(grid = grid, g_1 = g_1)
f1 = Convert_g1_To_f1(grid = grid, g_1 = g_1)
fR2 = Convert_gd_To_fR2(grid = grid, g_d = g_d, d = 3)
plot(grid, g_d, type = "l", xlim = c(0,10))
plot(grid, g_1, type = "l", xlim = c(0,10))
plot(Fg_1, xlim = c(-3,3))
plot(Qg_1, xlim = c(0.01,0.99))
plot(f1, xlim = c(-3,3))
plot(fR2, xlim = c(0,3))

[Package ElliptCopulas version 0.1.3 Index]