Displaying 20 results from an estimated 1200 matches similar to: "Inverse matrix using eigendecomposition"
2004 Nov 05
1
fast partial spectral decompositions.
hello,
i want to compute the top k eigenvalues+eigenvectors of a (large)
real symmetric matrix. since it doesn't look like any top-level R
function does this, i'll call LAPACK from a C shlib and then
use .Call. the only LAPACK function i see to do this in
R_ext/Lapack.h is dsyevx. however, i know that in LAPACK dsyevr
can also return a partial eigendecomposition. why is dsyevr not
2004 Nov 05
1
fast partial spectral decompositions.
hello,
i want to compute the top k eigenvalues+eigenvectors of a (large)
real symmetric matrix. since it doesn't look like any top-level R
function does this, i'll call LAPACK from a C shlib and then
use .Call. the only LAPACK function i see to do this in
R_ext/Lapack.h is dsyevx. however, i know that in LAPACK dsyevr
can also return a partial eigendecomposition. why is dsyevr not
2008 Mar 05
2
matrix inversion using solve() and matrices containing large/small values
Hello
I've stumbled upon a problem for inversion of a matrix with large values,
and I haven't found a solution yet... I wondered if someone could give a
hand. (It is about automatic optimisation of a calibration process, which
involves the inverse of the information matrix)
code:
*********************
> macht=0.8698965
> coeff=1.106836*10^(-8)
>
2012 Apr 25
1
pca biplot.princomp has a bug?
x=rmvnorm(2000, rep(0, 6), diag(c(5, rep(1,5))))
x=scale(x, center=T, scale=F)
pc <- princomp(x)
biplot(pc)
There are a bunch of red arrows plotted, what do they mean? I knew that the
first arrow labelled with "Var1" should be pointing the most varying
direction of the data-set (if we think them as 2000 data points, each being
a vector of size 6). I also read from
2004 Jul 19
2
8 bit characters and smbmount
Does somebody know how to handle 8bit characters ..?
I have problems with 8bit characters (ntilde, Otilde, etc)
I'm trying to copy from a spanish XP box to my linux (using smbmount)
and the system shows "Oacute" just as "O" and when copying I get
"No such file or directory" error.
I've tried
dos charset,
unix charset,
display
2005 May 02
14
eigenvalues of a circulant matrix
Hi,
It is my understanding that the eigenvectors of a circulant matrix are given as
follows:
1,omega,omega^2,....,omega^{p-1}
where the matrix has dimension given by p x p and omega is one of p complex
roots of unity. (See Bellman for an excellent discussion on this).
The matrix created by the attached row and obtained using the following
commands
indicates no imaginary parts for the
2001 Nov 06
2
Inverse Matrices
I have a problem with finding the inverse of a matrix. I have a square
9x9 matrix, A, and when I do solve(A) to find the inverse I get the
following error message:
Error in solve.default(A) : singular matrix `a' in solve
Has anybody got any ideas as to why this is happening?
Thanks
Laura Gross
_______________________________________________________________________
Never pay another
2004 Mar 11
0
A question about function "cor" in code C
Dear Sir:
I am interesting in to call function "cor" from C code. The reason for
this, is that I need to obtain a matrix of correlation in a C program, and I
have think to link my program in C code with R. But I don?t know make this
link. I have read R-exts.pdf document, but I have not found a direct way to
link.
But I have a problem which I have not found information in
2007 Feb 13
1
Questions about results from PCAproj for robust principal component analysis
Hi.
I have been looking at the PCAproj function in package pcaPP (R 2.4.1) for
robust principal components, and I'm trying to interpret the results. I
started with a data matrix of dimensions RxC (R is the number of rows /
observations, C the number of columns / variables). PCAproj returns a list
of class princomp, similar to the output of the function princomp. In a
case where I can
2008 Jun 18
2
highest eigenvalues of a matrix
DeaR list,
I happily use eigen() to compute the eigenvalues and eigenvectors of
a fairly large matrix (200x200, say), but it seems over-killed as its
rank is limited to typically 2 or 3. I sort of remember being taught
that numerical techniques can find iteratively decreasing eigenvalues
and corresponding orthogonal eigenvectors, which would provide a nice
alternative (once I have the
2002 Oct 09
3
Multiplication of Matrices
Hi,
Suppose I have a matrix, A. Is there an easy way to find A^{n}?
I mean, I can do something like:
A %*% A %*% A %*% A
for A^4, but if I want A^{10} it would be kind of annoying...
Cheers,
Kevin
------------------------------------------------------------------------------
Ko-Kang Kevin Wang
Postgraduate PGDipSci Student
Department of Statistics
University of Auckland
New Zealand
2013 Mar 14
2
Same eigenvalues but different eigenvectors using 'prcomp' and 'principal' commands
Dear all,
I've used the 'prcomp' command to
calculate the eigenvalues and eigenvectors of a matrix(gg).
Using the command 'principal' from the
'psych' packageĀ I've performed the same exercise. I got the same
eigenvalues but different eigenvectors. Is there any reason for that
difference?
Below are the steps I've followed:
1. PRCOMP
#defining the matrix
2005 Mar 14
1
r: eviews and r // eigen analysis
hi all
i have a question that about the eigen analysis found in R and in
eviews.
i used the same data set in the two packages and found different
answers. which is incorrect?
the data is:
aa ( a correlation matrix)
1 0.9801 0.9801 0.9801 0.9801
0.9801 1 0.9801 0.9801 0.9801
0.9801 0.9801 1 0.9801 0.9801
0.9801 0.9801 0.9801 1 0.9801
0.9801 0.9801 0.9801 0.9801 1
now
> svd(aa)
$d
[1] 4.9204
2011 Nov 14
2
How to compute eigenvectors and eigenvalues?
Hello.
Consider the following matrix:
mp <- matrix(c(0,1/4,1/4,3/4,0,1/4,1/4,3/4,1/2),3,3,byrow=T)
> mp
[,1] [,2] [,3]
[1,] 0.00 0.25 0.25
[2,] 0.75 0.00 0.25
[3,] 0.25 0.75 0.50
The eigenvectors of the previous matrix are 1, 0.25 and 0.25 and it is not a diagonalizable matrix.
When you try to find the eigenvalues and eigenvectors with R, R responses:
> eigen(mp)
$values
[1]
2011 Nov 14
0
Fwd: How to compute eigenvectors and eigenvalues?
Inicio del mensaje reenviado:
> De: Arnau Mir <arnau.mir@uib.es>
> Fecha: 14 de noviembre de 2011 13:24:31 GMT+01:00
> Para: Martin Maechler <maechler@stat.math.ethz.ch>
> Asunto: Re: [R] How to compute eigenvectors and eigenvalues?
>
> Sorry, but I can't explain very well.
>
>
> The matrix 4*mp is:
>
> 4*mp
> [,1] [,2] [,3]
> [1,]
2010 May 05
3
Symbolic eigenvalues and eigenvectors
Let's say I had a matrix like this:
library(Ryacas)
x<-Sym("x")
m<-matrix(c(cos (x), sin(x), -sin(x), cos(x)), ncol=2)
How can I use R to obtain the eigenvalues and eigenvectors?
Thanks,
John
[[alternative HTML version deleted]]
2008 Jun 03
3
matlab eigs function in R
Hello
Does anybody know how one can compute d largest eigenvalues/eigenvectors in
R, like in MATLAB eigs function ? eigen function computes all
eigenvectors/eigenvalues, and they are slightly different than those
generated by matlab eigs.
Thanks in advance
--
View this message in context: http://www.nabble.com/matlab-eigs-function-in-R-tp17619641p17619641.html
Sent from the R help mailing list
2003 Nov 04
2
real eigenvectors
Hello list,
Sorry, these questions are not directly linked to R.
If I consider an indefinte real matrix, I would like to know if the
symmetry of the matrix is sufficient to say that their eigenvectors are real ?
And what is the conditions to ensure that eigenvectors are real in the case
of an asymmetric matrix (if some conditions exist)?
Thanks in Advance,
St?phane DRAY
2011 Feb 01
2
better way to iterate matrix multiplication?
I'm simulating a Markov process using a vector of proportions. Each
value in the vector represents the proportion of the population who are
in a particular state (so the vector sums to 1). I have a square matrix
of transition probabilities, and for each tick of the Markov clock the
vector is multiplied by the transition matrix.
To illustrate the sort of thing I mean:
pm <-
2010 Jan 11
3
Eigenvectors and values in R and SAS
Hi,
I was wondering if function eigen() does something different from the
function call eigen() in SAS.
I'm in the process of translating a SAS code into a R code and the values of
the eigenvectors and eigenvalues of a square matrix came out to be different
from the values in SAS.
I would also appreciate it if someone can explain the difference in simple
terms. I'm pretty new to both