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lu(x, ...)
## S3 method for class 'dgeMatrix':
lu(x, warnSing = TRUE, \dots)
x
is a
"denseMatrix "
) logical specifying if a warning
should be signalled when x
is singular."LU"
, i.e., "denseLU "
or "sparseLU"
, see sparseLU
; this is
a representation of a triangular decomposition of x
.lu()
is a generic function with special methods for different types
of matrices. Use showMethods("lu")
to list all the methods
for the lu
generic. The method for class
(and all dense
matrices) is based on LAPACK's "dgetrf"
subroutine. It returns
a decomposition also for singular matrices.
The method for class
(and all sparse
matrices) is based on functions from the CSparse library. It signals
an error when the decomposition algorithm fails, as when x
is
(too close to) singular.
Tim Davis (2005)
Timothy A. Davis (2006)
Direct Methods for Sparse Linear Systems, SIAM Series
LU
and sparseLU
and function expand
;
qr
, chol
.##--- Dense -------------------------
x <- Matrix(rnorm(9), 3, 3)
lu(x)
##--- Sparse ------------------------
pm <- as(readMM(system.file("external/pores_1.mtx",
package = "Matrix")),
"CsparseMatrix")
str(pmLU <- lu(pm)) # p is a 0-based permutation of the rows
# q is a 0-based permutation of the columns
## permute rows and columns of original matrix
ppm <- pm[pmLU@p + 1L, pmLU@q + 1L]
pLU <- pmLU@L %*% pmLU@U
## equal up to "rounding"
ppm[1:14, 1:5]
pLU[1:14, 1:5] # product can have extra zeros
## "prove" consistency (up to rounding):
i0 <- ppm != pLU & ppm == 0
iN <- ppm != pLU & ppm != 0
stopifnot(all(abs((ppm - pLU)[i0]) < 1e-7), # absolute error for true 0
all(abs((ppm - pLU)[iN]/ppm[iN]) < 1e-9)) # relative error
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