Description Usage Arguments Value Examples
Selects bandwidth for sample covariance matrix by k-fold cross validation
1 | banded.sample.cv(X, bandwidth, folds = 3, est.eval = TRUE, Frob = TRUE)
|
X |
A data matrix with n rows and p columns. Rows are assumed to be independent realizations from a p-variate distribution with covariance Σ. |
bandwidth |
A vector of candidate bandwidths. Candidate bandwidths can only positive integers such that the maximum is less than p-1 |
.
folds |
The number of folds used for cross validation. Default is |
est.eval |
Logical: |
Frob |
Logical: |
A list with
bandwidth.min |
the bandwidth minimizing cv error |
est |
the sample covariance matrix at bandwidth.min |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ## set sample size and dimension
n=20
p=100
## create covariance with AR1 structure
Sigma = matrix(0, nrow=p, ncol=p)
for(l in 1:p){
for(m in 1:p){
Sigma[l,m] = .5^(abs(l-m))
}
}
## simulation Normal data
eo1 = eigen(Sigma)
Sigma.sqrt = eo1$vec%*%diag(eo1$val^.5)%*%t(eo1$vec)
X = t(Sigma.sqrt%*%matrix(rnorm(n*p), nrow=p, ncol=n))
## perform cross validation
k = 4:7
out2.cv = banded.sample.cv(X, bandwidth=k, folds=5)
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