roc.simu: Simulate the ROC
In DongyueXie/scca: Sparse Canonical Correlation Analysis - Intergrated Methods

A function to run the simulation for plotting ROC

roc.simu(nroc = 1, u, v, n = 50, data.type = "normal", sigma_z = 1,
  sigma_x = NULL, sigma_y = NULL, theta = 0.01, n_x = 1000,
  n_y = 1000, lambda_z = 10, maxstep_s0 = NULL, penaltyx = seq(0, 1,
  length.out = 50), penaltyy = seq(0, 1, length.out = 50), alpha.u = seq(0,
  1, length.out = 10), alpha.v = seq(0, 1, length.out = 10), nlambda = 20,
  edgex, edgey, plain = T, maxstep_gs = 20, gamma.u = seq(0, 5, length.out
  = 10), gamma.v = seq(0, 5, length.out = 10), seed = 12345)

`maxstep_s0, maxstep_gs:`	paramters for s0cca and gscca
`penaltyx, penaltyy:`	for s1cca, vectors
`alpha.u, alpha.v, nlambda:`	for enscca, vector, vector, scalar.
`gamma.u, gamma.v:`	paramters for gscca, vectors.
`nroc:`	the number of iterations
`data.type:`	type of data to generate, choose from 'normal','normal_oth','normal_oth'...