banded.sample {FastBandChol} | R Documentation |
Estimates a covariance matrix by banding the sample covariance matrix
banded.sample(X, bandwidth, centered = FALSE)
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 positive integer. Must be less than p-1. |
.
centered |
Logical. Is data matrix centered? Default is |
A list with
est |
The estimated covariance matrix. |
## 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)) ## compute estimate out2 = banded.sample(X, bandwidth=4)