simulate_lsr: Simulate Heterogeneous, Low-Rank, and Sparse Data

In mixedLSR: Mixed, Low-Rank, and Sparse Multivariate Regression on High-Dimensional Data

Simulate Heterogeneous, Low-Rank, and Sparse Data

Description

Simulate Heterogeneous, Low-Rank, and Sparse Data

Usage

simulate_lsr(
  N = 100,
  k = 2,
  p = 30,
  m = 35,
  b = 1,
  d = 20,
  h = 0.2,
  case = "independent"
)

Arguments

N	The sample size, default = 100.
k	The number of groups, default = 2.
p	The number of predictor features, default = 30.
m	The number of response features, default = 35.
b	The signal-to-noise ratio, default = 1.
d	The singular value, default = 20.
h	The lower bound for the singular matrix simulation, default = 0.2.
case	The covariance case, "independent" or "dependent", default = "independent".

Value

A list of simulation values, including x matrix, y matrix, coefficients and true clustering assignments.

Examples

simulate_lsr()

mixedLSR documentation built on Nov. 10, 2022, 6:17 p.m.