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2009 Jun 17
1
Inverting a square matrix using solve() with LAPACK=TRUE (PR#13762)
...l_Name: Ravi Varadhan
Version: 2.8.1
OS: Windows
Submission from: (NULL) (162.129.251.19)
Inverting a matrix with solve(), but using LAPACK=TRUE, gives erroneous
results:
Here is an example:
hilbert <- function(n) { i <- 1:n; 1 / outer(i - 1, i, "+") }
h5 <- hilbert(5)
hinv1 <- solve(qr(h5))
hinv2 <- solve(qr(h5, LAPACK=TRUE))
all.equal(hinv1, hinv2) # They are not equal
Here is a function that I wrote to correct this problem:
solve.lapack <- function(A, LAPACK=TRUE, tol=1.e-07) {
# A function to invert a matrix using "LAPACK" or "LINPAC...
2009 Jun 18
1
Inverting a square... (PR#13762)
...(p)]
which should be [seq_len(p),]
(otherwise, in the matrix case, the RHS will recycle only the 1st p
elements, i.e., the 1st column).
>=20
> Here is an example:
>=20
> hilbert <- function(n) { i <- 1:n; 1 / outer(i - 1, i, "+") }
> h5 <- hilbert(5)
> hinv1 <- solve(qr(h5))
> hinv2 <- solve(qr(h5, LAPACK=3DTRUE))=09
> all.equal(hinv1, hinv2) # They are not equal
>=20
> Here is a function that I wrote to correct this problem:
>=20
> solve.lapack <- function(A, LAPACK=3DTRUE, tol=3D1.e-07) {
> # A function to invert a...
2009 Jun 18
0
Inverting a square matrix using solve() with LAPACK=TRUE (PR#13765)
...len(p)]
which should be [seq_len(p),]
(otherwise, in the matrix case, the RHS will recycle only the 1st p
elements, i.e., the 1st column).
>
> Here is an example:
>
> hilbert <- function(n) { i <- 1:n; 1 / outer(i - 1, i, "+") }
> h5 <- hilbert(5)
> hinv1 <- solve(qr(h5))
> hinv2 <- solve(qr(h5, LAPACK=TRUE))
> all.equal(hinv1, hinv2) # They are not equal
>
> Here is a function that I wrote to correct this problem:
>
> solve.lapack <- function(A, LAPACK=TRUE, tol=1.e-07) {
> # A function to invert a matrix using...
2009 Jun 17
3
Matrix inversion-different answers from LAPACK and LINPACK
Hello.
I am trying to invert a matrix, and I am finding that I can get different
answers depending on whether I set LAPACK true or false using "qr". I had
understood that LAPACK is, in general more robust and faster than LINPACK,
so I am confused as to why I am getting what seems to be invalid answers.
The matrix is ostensibly the Hessian for a function I am optimizing. I want
to get