| simulData {LINselect} | R Documentation |
Function to simulate data Y = X β + σ N(0, 1)
simulData(p = 100, n = 100, beta = NULL, C = NULL, r = 0.95,
rSN = 10)
p |
integer : number of variates. Should be >15 if |
n |
integer : number of observations |
beta |
vector with |
C |
matrix |
r |
scalar for calculating the covariance of X when |
rSN |
scalar : ratio signal/noise |
When beta is NULL, then p should be
greater than 15 and
beta=c(rep(2.5,5),rep(1.5,5),rep(0.5,5),rep(0,p-15))
When C is NULL, then C is block
diagonal with
C[a,b] = r**abs(a-b) for 1 ≤ a, b ≤ 15
C[a,b] = r**abs(a-b) for 16 ≤ a, b ≤ p
The lines of X are n i.i.d. gaussian variables with
mean 0 and covariance matrix C.
The variance sigma**2 equals the squared euclidean
norm of X β divided by rSN*n.
A list with components :
Y |
vector |
X |
matrix |
C |
matrix |
sigma |
scalar. See details. |
beta |
vector with |
Library mvtnorm is loaded.
Yannick Baraud, Christophe Giraud, Sylvie Huet