Simulated data from a DGP with an underlying causal relationship between
covariates X and the target y.
The covariates matrix X consists of 10 variables whose effect size on target
y is defined by the vector
c(1, -0.83, 0.67, -0.5, 0.33, -0.17, 0, ..., 0)
with the first six effect sizes decreasing in absolute terms continuously
from 1 to 0 and alternating in their sign.
The true causal effect of all other covariates is 0.
The variables in X follow a normal distribution with mean zero while the
covariance matrix follows a Toeplitz matrix.
The target y is then a linear transformation of X plus a vector of standard
normal random variables (i.e. error term).
(See vignette for more details.)