In those Copula codes you can get a rough idea what copula is, how to estimate and simulate it, how to test its performance, etc., to help you visualize what on earth the copula should look like, below R code draws plots of some widely used copulas.
http://www.math.tu-berlin.de/~mkeller/index.php?target=rcode
R code
Programs I wrote for the statistical computing environment R. Note that I am no longer actively maintaining the code.
Download Option Data and Plot Smiles
This R program can be used to download option price data from Yahoo to a data frame and to plot the corresponding implied-volatility smiles. Requires package ‘fCalendar’. After downloading and sourcing the file try the following lines of code:
opt <- yahoo.getAllOptions("IBM") ## download data
summary(opt) ## data overview
plot.smile(opt) ## plot 2d volatility smiles
plot3d.smile(opt) ## plot 3d volatility smiles
Visualize Levy Processes
This R program contains functions to plot trajectories of several Levy processes. The processes implemented are alpha-stable processes, Variance-Gamma and Normal-Inverse-Gaussian processes. Requires packages ‘SuppDists’ and ‘fBasics’. After downloading and sourcing the file try the following lines of code:
plot.multi(stable.proc,alpha=1.7,beta=1) ## Stable process
plot.multi(VG.proc,sigma=0.2,theta=1,kappa=0.1) ## Variance Gamma process with drift
plot.multi(NIG.proc,sigma=0.2,theta=0,kappa=0.1) ## Normal Inverse Gaussian process
Visualize Some Copulas
This R program draws some plots of frequently used copulas. Just execute the R-code directly.