Diagonal {Matrix} | R Documentation |
Create a diagonal matrix object, i.e., an object inheriting from
diagonalMatrix
(or a sparse diagonal matrix in
cases that is prefered).
Diagonal(n, x = NULL) .symDiagonal(n, x = rep.int(1,n), uplo = "U", kind = if(is.logical(x)) "l" else "d") .trDiagonal(n, x = 1, uplo = "U", unitri=TRUE, kind = if(is.logical(x)) "l" else "d") .sparseDiagonal(n, x = 1, uplo = "U", shape = if(missing(cols)) "t" else "g", unitri, kind, cols = if(n) 0:(n - 1L) else integer(0))
n |
integer specifying the dimension of the (square) matrix. If
missing, |
x |
numeric or logical; if missing, a unit diagonal n x n matrix is created. |
uplo |
for |
shape |
string of 1 character, one of |
unitri |
optional logical indicating if a triangular result
should be “unit-triangular”, i.e., with |
kind |
string of 1 character, one of |
cols |
integer vector with values from |
Diagonal()
returns an object of class
ddiMatrix
or ldiMatrix
(with “superclass” diagonalMatrix
).
.symDiagonal()
returns an object of class
dsCMatrix
or lsCMatrix
,
i.e., a sparse symmetric matrix. Analogously,
.triDiagonal
gives a sparse triangularMatrix
.
This can be more efficient than Diagonal(n)
when the result is combined
with further symmetric (sparse) matrices, e.g., in kronecker
,
however not for
matrix multiplications where Diagonal()
is clearly preferred.
.sparseDiagonal()
, the workhorse of .symDiagonal
and
.trDiagonal
returns
a CsparseMatrix
(the resulting class depending
on shape
and kind
) representation of Diagonal(n)
,
or, when cols
are specified, of Diagonal(n)[, cols+1]
.
Martin Maechler
the generic function diag
for extraction
of the diagonal from a matrix works for all “Matrices”.
bandSparse
constructs a banded sparse matrix from
its non-zero sub-/super - diagonals. band(A)
returns a
band matrix containing some sub-/super - diagonals of A
.
Matrix
for general matrix construction;
further, class diagonalMatrix
.
Diagonal(3) Diagonal(x = 10^(3:1)) Diagonal(x = (1:4) >= 2)#-> "ldiMatrix" ## Use Diagonal() + kronecker() for "repeated-block" matrices: M1 <- Matrix(0+0:5, 2,3) (M <- kronecker(Diagonal(3), M1)) (S <- crossprod(Matrix(rbinom(60, size=1, prob=0.1), 10,6))) (SI <- S + 10*.symDiagonal(6)) # sparse symmetric still stopifnot(is(SI, "dsCMatrix")) (I4 <- .sparseDiagonal(4, shape="t"))# now (2012-10) unitriangular stopifnot(I4@diag == "U", all(I4 == diag(4)))