matrix r random

# Make a random correlation matrix semi definite positive

I am trying to make a random matrix correlation over 183 variables to calculate a Cholesky decomposition and correlate 183 random normals. For the creation of the correlation matrix the following reproducible code is the one I am using:

First I set the seed

``````set.seed(2)
``````

Then I generate random numbers between 0.6 and 0.8

``````corr <- matrix(runif(183*183, min = 0.6, max = 0.8), 183, 183)
``````

The next step is turning the diagonal into ones

``````for (i in 1:183) {
for (j in 1:183) {
if (i == j) {
corr[i,j] <- 1
}
}
}
``````

Last step is making it symmetric

``````for (i in 1:183) {
for (j in 1:183) {
if (i < j) {
corr[i,j] <- corr[j,i]
}
}
}
``````

The problem I run into arise when I try to make the cholesky decomposition

``````cholesky <- chol(corr)
``````

I get the following error:

Error in chol.default(corr) : the leading minor of order 14 is not positive definite

How could I make my correlation matrix semi definite positive?

Questioner
Mauro
Viewed
68
ThomasIsCoding 2020-01-31 17:07

Maybe you can try the code below to generate semi-definite positive matrix

``````set.seed(2)
v <- runif(183,0.6,0.8)
corr <- `diag<-`(tcrossprod(v),1)
``````