\name{Schur} \title{Schur Decomposition of a Matrix} \usage{ Schur(x, vectors, \dots) } \alias{Schur} \alias{Schur,dgeMatrix,logical-method} \alias{Schur,dgeMatrix,missing-method} \alias{Schur,diagonalMatrix,logical-method} \alias{Schur,diagonalMatrix,missing-method} \alias{Schur,triangularMatrix,logical-method} \alias{Schur,triangularMatrix,missing-method} \alias{Schur,dsyMatrix,ANY-method} \alias{Schur,generalMatrix,ANY-method} \alias{Schur,symmetricMatrix,ANY-method} \description{ Computes the Schur decomposition and eigenvalues of a square matrix; see the BACKGROUND information below. } \arguments{ \item{x}{ numeric (or complex, in future) square Matrix (inheriting from class \code{"Matrix"}). Missing values (NAs) are not allowed. } \item{vectors}{logical. When \code{TRUE} (the default), the Schur vectors are computed, and the result is a proper \code{\linkS4class{MatrixFactorization}} of class \code{\linkS4class{Schur}}. } \item{\dots}{further arguments passed to or from other methods.} } \value{ If \code{vectors} are \code{TRUE}, as per default, an object of class \code{\linkS4class{Schur}}. If \code{vectors} are \code{FALSE}, a list with components \item{T}{the upper quasi-triangular (square) matrix of the Schur decomposition.} \item{EValues}{the vector of \code{\link{numeric}} or \code{\link{complex}} eigen values of \eqn{T} or \eqn{A}.} } \details{ Based on the Lapack subroutine \code{dgees}. } \section{BACKGROUND}{ If \code{A} is a square matrix, then \code{A = Q T t(Q)}, where \code{Q} is orthogonal, and \code{T} is upper block-triangular (nearly triangular with either 1 by 1 or 2 by 2 blocks on the diagonal) where the 2 by 2 blocks correspond to (non-real) complex eigenvalues. The eigenvalues of \code{A} are the same as those of \code{T}, which are easy to compute. The Schur form is used most often for computing non-symmetric eigenvalue decompositions, and for computing functions of matrices such as matrix exponentials. } \references{ Anderson, E., et al. (1994). \emph{LAPACK User's Guide,} 2nd edition, SIAM, Philadelphia. } \examples{ Schur(Hilbert(9)) # Schur factorization (real eigenvalues) (A <- Matrix(round(rnorm(5*5, sd = 100)), nrow = 5)) (Sch.A <- Schur(A)) eTA <- eigen(Sch.A@T) str(SchA <- Schur(A, vectors=FALSE))# no 'T' ==> simple list stopifnot(all.equal(eTA$values, eigen(A)$values, tol = 1e-13), all.equal(eTA$values, local({z <- Sch.A@EValues z[order(Mod(z), decreasing=TRUE)]}), tol = 1e-13), identical(SchA$T, Sch.A@T), identical(SchA$EValues, Sch.A@EValues)) } \keyword{algebra}