I have a circulant correlation matrix that has only positive entries. (Because it is a correlation matrix, it is symmetric with diagonal entries of 1.) I am wondering about the entries of the square root matrix of this circulant correlation matrix has only positive entries. I tried with a bunch of autoregressive correlation matrices and am able to show the result. However, I was wondering if such a result exists, or if even a restrictive version exists and how one goes about proving this.
Here is my R code for my experiments:
circulant.1d.corr <- function(n, rho)
#creates 1d AR sequence of length n (periodic in length)
{
ff <- c(1, rho^(1:(n/2)))
ff <- c(ff, rev(ff[2:((n + 1)/2)]))
ff
}
make.circ.mat <- function(n, rho) {
x <- circulant.1d.corr(n, rho)
R <- NULL
for (i in 1:n) {
if (i > 1) x <- c(x[n], x[-n])
R <- rbind(R, x)
}
R
}
Rhalf.circ <- function(n, rho) {
R <- make.circ.mat(n, rho)
R.eigen <- eigen(R, symmetric = T)
R.eigen$vectors %*% diag(sqrt(R.eigen$values)) %*% t(R.eigen$vectors)
}
> Rhalf.circ(10, 0.05)[1,]
[1] 9.993743e-01 2.499218e-02 9.373043e-04 3.905640e-05 1.708390e-06
[6] -2.359698e-09 1.708390e-06 3.905640e-05 9.373043e-04 2.499218e-02
> Rhalf.circ(10, 0.1)[1,]
[1] 9.974890e-01 4.993711e-02 3.746853e-03 3.123054e-04 2.730579e-05
[6] -6.763812e-08 2.730579e-05 3.123054e-04 3.746853e-03 4.993711e-02
> Rhalf.circ(10, 0.25)[1,]
[1] 9.839308e-01 1.239837e-01 2.331028e-02 4.864143e-03 1.059005e-03
[6] -1.104196e-06 1.059005e-03 4.864143e-03 2.331028e-02 1.239837e-01
> Rhalf.circ(10, 0.5)[1,]
[1] 0.9293938767 0.2407913830 0.0915253610 0.0384984646 0.0165463712
[6] 0.0006556758 0.0165463712 0.0384984646 0.0915253610 0.2407913830
> Rhalf.circ(10, 0.75)[1,]
[1] 0.80511919 0.33654932 0.19870997 0.12794897 0.08148659 0.01608999
[7] 0.08148659 0.12794897 0.19870997 0.33654932
> Rhalf.circ(10, 0.9)[1,]
[1] 0.64488327 0.36788703 0.27640050 0.21993968 0.17083677 0.07437758
[7] 0.17083677 0.21993968 0.27640050 0.36788703
> Rhalf.circ(10, 0.95)[1,]
[1] 0.5505803 0.3657788 0.3022261 0.2598229 0.2183690 0.1273030 0.2183690
[8] 0.2598229 0.3022261 0.3657788
>
Then, but for very small values, the entries of the square root matrix are positive.
I am calculating the square root of a matrix through its spectral decomposition.
Any pointers on the existence of this result (even a restricted version, such as decreasing AR(1) structure, which is the example in the R code above) or how to go about proving this is greatly appreciated.