1d:T7b9,# External matrices operations. A set of routines to operate on "external" matrices. ```r is.extmat(X) extmat.ncol(X) extmat.nrow(X) extmat(mul, tmul, nrow, ncol, env = parent.frame()) ematmul(emat, v, transposed = FALSE) ``` ## Arguments - `X, emat`: matrix to operate on - `mul`: function performing the multiplication of matrix to vector - `tmul`: function performing the multiplication of transposed matrix to vector - `nrow`: number of rows of the matrix - `ncol`: number of columns of the matrix - `env`: environment, where matrix-vector multiplication function call is evaluated in - `transposed`: logical, if 'TRUE' the multiplication is performed with the transposed matrix. - `v`: vector to multiply with. ## Details These routines checks whether the given external pointer actually points to "external matrix" structure and allow to extract the number of columns and rows respectively. 'extmat' is a convenient wrapper which allows one provide just the routines which will multiply with matrix and the transposed one (e.g. if the matrix is sparse or structured) and allow to use the SVD routines of the package ## Returns Object 'extmat' class ## Examples ```r ## Not run: library(Matrix) f <- function(v) as.numeric(A %*% v) # Convert Matrix object back to vector tf <- function(v) as.numeric(tA %*% v) # Convert Matrix object back to vector e <- new.env() assign("A", USCounties, e) assign("tA", t(USCounties), e) environment(f) <- e environment(tf) <- e m <-extmat(f, tf, nrow(USCounties), ncol(USCounties)) system.time(v1 <- propack.svd(m, neig = 10)) # user system elapsed # 0.252 0.007 0.259 system.time(v2 <- propack.svd(as.matrix(USCounties), neig = 10)) # user system elapsed # 8.563 0.027 8.590 ## End(Not run) # The largest eigenvalue and the corresponding eigenvector of a Hilbert matrix h <- outer(1:5000, 1:5000, function(i, j) 1 / (i + j - 1)) v1 <- trlan.eigen(h, neig = 1) print(v1$d) ``` ## See Also `extmat`

extmat function