swh:1:snp:81eadaa089e8253d8469bcef66aa332632c6c669
Tip revision: fdf16693b000f3e309c56091892c61f0ec9fd670 authored by Hans W. Borchers on 21 November 2017, 16:15:00 UTC
version 2.1.1
version 2.1.1
Tip revision: fdf1669
normest.R
##
## n o r m e s t . R Matrix Norm estimation
##
normest <- function(M, maxiter = 100, tol = .Machine$double.eps^(1/2)) {
if (length(M) == 0)
return(0)
if (!is.numeric(M))
stop("Argument 'M' must be a numeric matrix.")
if (is.vector(M))
M <- matrix(c(M), nrow = length(M), ncol = 1)
x <- matrix(apply(abs(M), 2, sum), ncol = 1)
est <- norm(x, "F") # Frobenius Norm
if (est == 0) return(0)
x <- x/est
est0 <- 0
niter <- 0
while (abs(est - est0) > tol * est && niter <= maxiter) {
est0 <- est
Mx <- M %*% x
if (all(Mx == 0))
Mx <- matrix(runif(length(Mx)), ncol(Mx), nrow(Mx))
x <- t(M) %*% Mx
normx <- norm(x, "F")
est <- normx / norm(Mx, "F")
x <- x / normx
niter <- niter + 1
}
if (niter > maxiter)
warning("Number of iterations exceeded 'maxiter'.")
return(est)
}