datagen.norm {PoSIAdjRSquared} | R Documentation |
Data generation normal
Description
Function to generate data according to the linear model of the form Y = X*beta + epsilon where the noise epsilon follows a standard normal distribution.
Usage
datagen.norm(seed, n, p, rho, beta_vec)
Arguments
seed |
Integer for seed |
n |
Integer for sample size |
p |
Integer for number of variables in the design matrix |
rho |
Integer for correlation between variables in the design matrix |
beta_vec |
True regression coefficient vector of length p |
Value
X |
Design matrix of type "matrix" and dimension nxp |
y |
Response vector of type "matrix" and dimension nx1 |
true_y |
True response vector, i.e. without the noise, of type "matrix" and dimension nx1 |
Examples
datagen.norm(seed = 7, n = 100, p = 10, rho = 0, beta_vec = c(1,0.5,0,0.5,0,0,0,0,0,0))
[Package PoSIAdjRSquared version 0.1.0 Index]