Similar to the the SRRR simulation model in Chen and Huang (2012), JASA
rrr.sim2(
n = 100,
p = 50,
p0 = 10,
q = 50,
q0 = 10,
nrank = 3,
s2n = 1,
sigma = NULL,
rho_X = 0.5,
rho_E = 0
)sample size
number of predictors
number of relevant predictors
number of responses
number of relevant responses
model rank
signal to noise ratio
error variance. If specfied, then s2n has no effect
correlation parameter in the generation of predictors
correlation parameter in the generation of random errors
similated model and data
Chen, L. and Huang, J.Z. (2012) Sparse reduced-rank regression for simultaneous dimension reduction and variable selection. Journal of the American Statistical Association, 107:500, 1533--1545.