Code borrowed from SLOPE package for generating datasets

Code borrowed from SLOPE package for generating datasets

randomProblem(
  n = 1000,
  p = 100,
  q = 0.2,
  n_groups = NULL,
  n_targets = if (match.arg(response) == "multinomial") 3 else 1,
  density = 0,
  amplitude = if (match.arg(response) == "poisson") 1 else 3,
  alpha = 1,
  response = c("gaussian", "binomial", "poisson", "multinomial"),
  rho = 0
)

Arguments

n	Number of data points
p	Number of features
q	Parameter controlling lambda sequence
n_groups	Number of groups of predictors
n_targets	Dimension of response variable
density	Determine sparsity of the data generated. Default set to 0.
amplitude	Scale of coefficient in output
alpha	Standard deviation
response	Choice of likelohood function
rho	Correlation