data.generation: Data generation

In mgerus/ABSLOPE: High-dimensional Model Selection with Missing Values

Description

Generate dataset with missing values

Usage

data.generation(n = 100, p = 100, nspr = 10, p.miss = 0.1,
  mu = rep(0, p), Sigma = toeplitz(0^(0:(p - 1))), signallevel = 3,
  mec = "MCAR", sigma = 1, scale = TRUE)

Arguments

n	Observation number
p	Dimenaion
nspr	Non-sparsity
p.miss	Percentage of missingness
mu	Mean of covariates
Sigma	Covariance of covariates
signallevel	Signal magnitude
mec	Missing mechanism
sigma	noise variance
scale	If TRUE, perform scaling after generating dataset.

Examples

data.list = data.generation()
X = data.list$X.obs
y = data.list$y

mgerus/ABSLOPE documentation built on Nov. 13, 2019, 12:34 a.m.