http://www.mathworks.com/matlabcentral/fileexchange/3910

這裡可能有解答,希望有幫上忙

不知道你用的什么版本的matlab 在最新版中有个函数 直接就可以求到！

函数是：

copulaparam

Copula parameters as function of rank correlation

Syntax

rho = copulaparam('Gaussian',R)
rho = copulaparam('t',R,NU)
alpha = copulaparam(family,R)
[...] = copulaparam(...,'type',type)

比如：

Get the linear correlation coefficient corresponding to a bivariate Gaussian copula having a rank correlation of -0.5.

tau = -0.5 rho = copulaparam('gaussian',tau) rho = -0.7071 % Generate dependent beta random values using that copula u = copularnd('gaussian',rho,100); b = betainv(u,2,2); % Verify that the sample has a rank correlation % approximately equal to tau tau_sample = corr(b,'type','k') tau_sample = 1.0000 -0.4638 -0.4638 1.0000