data.sim: High Dimensional Correlated Data Generation

In BinaryEMVS: Variable Selection for Binary Data Using the EM Algorithm

Description

Generates an high dimensional dataset with a subset of columns being related to the response, while controlling the maximum correlation between related and unrelated variables.

Usage

data.sim(n = 100, p = 1000, pr = 3, cor = 0.6)

Arguments

n	sample size
p	total number of variables
pr	the number of variables related to the response
cor	the maximum correlation between related and unrelated variables

Value

Returns an nxp matrix with the first pr columns having maximum correlation cor with the remaining p-pr columns

Examples

data=data.sim(n=100,p=1000,pr=10,cor=.6)
max(abs(cor(data))[abs(cor(data))<1])

BinaryEMVS documentation built on May 2, 2019, 2:09 p.m.