Displaying 20 results from an estimated 1340 matches for "symmetrical".
2011 Oct 23
0
FW: Re: symmetric matrix multiplication
Just to avoid possible confusion, let me correct a typo
(at step [2] in the example below). Apologies!
-----FW: <XFMail.111023084327.ted.harding at wlandres.net>-----
Date: Sun, 23 Oct 2011 08:43:27 +0100 (BST)
Sender: r-help-bounces at r-project.org
From: (Ted Harding) <ted.harding at wlandres.net>
To: r-help at r-project.org
Subject: Re: [R] symmetric matrix multiplication
On
2013 Jun 18
1
eigen(symmetric=TRUE) for complex matrices
R-3.0.1 rev 62743, binary downloaded from CRAN just now; macosx 10.8.3
Hello,
eigen(symmetric=TRUE) behaves strangely when given complex matrices.
The following two lines define 'A', a 100x100 (real) symmetric matrix
which theoretical considerations [Bochner's theorem] show to be positive
definite:
jj <- matrix(0,100,100)
A <- exp(-0.1*(row(jj)-col(jj))^2)
A's being
2005 May 01
2
eigen() may fail for some symmetric matrices, affects mvrnorm()
Hi all,
Recently our statistics students noticed that their Gibbs samplers were
crashing due to some NaNs in some parameters. The NaNs came from
mvrnorm (Ripley & Venables' MASS package multivariate normal sampling
function) and with some more investigation it turned out that they were
generated by function eigen, the eigenvalue computing function. The
problem did not seem to happen
2007 Jul 28
8
generating symmetric matrices
Greetings,
I have a seemingly simple task which I have not been able to solve today. I want to construct a symmetric matrix of arbtriray size w/o using loops. The following I thought would do it:
p <- 6
Rmat <- diag(p)
dat.cor <- rnorm(p*(p-1)/2)
Rmat[outer(1:p, 1:p, "<")] <- Rmat[outer(1:p, 1:p, ">")] <- dat.cor
However, the problem is that the matrix
2000 May 10
4
Q: Problems with eigen() vs. svd()
At 01:37 PM 5/10/00 +0200, ralle wrote:
>Hi,
>I have a problem understanding what is going on with eigen() for
>nonsymmetric matrices.
>Example:
>h<-rnorm(6)
>> dim(h)<-c(2,3)
>> c<-rnorm(6)
"c" is not a great choice of identifier!
>> dim(c)<-c(3,2)
>> Pi<-h %*% c
>> eigen(Pi)$values
>[1] 1.56216542 0.07147773
These could
2009 Apr 24
4
Long string in crypting
I use a solution to crypt a string that I found using OpenSSL. But the
crypted string becomes very long, too long for a varchar 255 to hold it.
What can I do to make it shorter? Or should I just use text as column in
the mysql db?
public_key_file = ''lib/public.pem''
public_key = OpenSSL::PKey::RSA.new(File.read(public_key_file))
@encrypted_string =
2011 Jan 20
2
splitting a square symmetric matrix
So many matrices are square symmetrical (i.e. variance-covariance matrices),
is there any way to get R to split the matrix on its diagonal and just
return one diagonal?
So if I have
mat<-matrix(c(1,4,3,4,1,2,3,2,1), nrow = 3, ncol=3, byrow=TRUE)
is there anyway to get the lower right diagonal instead of the entire
symmetri...
2011 Oct 23
1
symmetric matrix multiplication
I have a symmetric matrix B (17x17), and a (17x17) square matrix A. If do
the following matrix multiplication I SHOULD get a symmetric matrix, however
i don't. The computation required is:
C = t(A)%*%B%*%A
here are some checks for symmetry
> (max(abs(B - t(B))))
[1] 0
> C = t(A)%*%B%*%A
> (max(abs(C - t(C))))
[1] 3.552714e-15
Any help on the matter would be very much appreciated.
2005 May 30
3
how to invert the matrix with quite small eigenvalues
Dear all,
I encounter some covariance matrix with quite small eigenvalues
(around 1e-18), which are smaller than the machine precision. The
dimension of my matrix is 17. Here I just fake some small matrix for
illustration.
a<-diag(c(rep(3,4),1e-18)) # a matrix with small eigenvalues
b<-matrix(1:25,ncol=5) # define b to get an orthogonal matrix
b<-b+t(b)
bb<-eigen(b,symmetric=T)
2004 Oct 05
0
SIP and symmetric NAT
Hello,
I have a problem with a Grandstream being behind a symmetric nat. The
box which does the nat is a german "Fritz Box". This one does nat for
the internal network. In the internal network is a Granstream
BudgeTone 100. The nat router has a dial-up connection, so ip changes
on every dial-in.
|------------| |------------| |--------|
|Grandstream
2013 Feb 05
2
adjacency list to non-symmetric matrix
Dear R community,
is there an easy way to convert an adjacency list (or a data-frame) to a non-symmetric matrix?
The adjacency list has the following form:
person group
1 Sam a
2 Sam b
3 Sam c
4 Greg a
5 Tom b
6 Tom c
7 Tom d
8 Mary b
9 Mary d
I need the data in a matrix with persons as rows and groups as columns:
a b c d
Sam 1 1 1 0
Greg 1 0 0 0
Tom 0 1 1 1
Mary 0 1 0 1
I know that there
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
2010 Aug 03
4
Need help on upper.tri()
HI, I am really messing up to make a symmetrical matrix using upper.tri() & lower.tri() function. Here is my code:
> set.seed(1)
> mat = matrix(rnorm(25), 5, 5)
> mat
[,1] [,2] [,3] [,4] [,5]
[1,] -0.6264538 -0.8204684 1.5117812 -0.04493361 0.91897737
[2,] 0.1836433 0.4874291 0.3898432 -0.0...
2006 Mar 03
1
NA in eigen()
Hi,
I am using eigen to get an eigen decomposition of a square, symmetric
matrix. For some reason, I am getting a column in my eigen vectors (the
52nd column out of 601) that is a column of all NAs. I am using the option,
symmetric=T for eigen. I just discovered that I do not get this behavior
when I use the option EISPACK=T. With EISPACK=T, the 52nd eigenvector is
(up to rounding error) a
2006 Sep 26
2
about the determinant of a symmetric compound matrix
Dear R users,
even if this question is not related to an issue about R, probably some of you will be able to help me.
I have a square matrix of dimension k by k with alpha on the diagonal and beta everywhee else.
This symmetric matrix is called symmetric compound matrix and has the form
a( I + cJ),
where
I is the k by k identity matrix
J is the k by k matrix of all ones
a = alpha - beta
c =
2010 Apr 30
2
Flattening and unflattening symmetric matrices
Here's an easy question: I'd like to convert a symmetric matrix to a
vector composed of the upper.tri() part of it plus the diagonal, and
convert it back again. What's the best way to achieve this? I'm
wondering if there are some built in functions to do this easily. I
can encode fine:
v <- c(diag(A),A[upper.tri(A)])
but I don't see an easy way to recover A from v
2011 Apr 06
1
Creating a symmetric contingency table from two vectors with different length of levels in R
Hello,
How can I create a symmetric contingency table from two categorical vectors
having different length of levels?
For example one vector has 98 levels
TotalData1$Taxa.1
[1] "Aconoidasida" "Actinobacteria (class)"
"Actinopterygii" "Alphaproteobacteria"
[5] "Amoebozoa"
2010 Nov 08
1
Exponent of sqr symmetric matrix
Dear R experts,
I really have difficulty when I try to deal with this question.
suppose X is a square symmetric matrix. The exponent of X is defined by the
matrix limit as following:
exp(X) = lim (I + X/n)^n, note: the limit is from n to infinite.
How can I write R function for the above?
Thank you very much
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2006 Jan 04
5
habtm recusive
I have a people table:
CREATE TABLE people (
id int(10) unsigned NOT NULL auto_increment,
first_name varchar(75) default NULL,
middle_name varchar(75) default NULL,
last_name varchar(75) default NULL,
PRIMARY KEY (id)
) ENGINE=MyISAM DEFAULT CHARSET=latin1 AUTO_INCREMENT=1272 ;
and a people_people table:
CREATE TABLE people_people (
person_id int(11) unsigned NOT NULL,
2009 Jan 07
2
Memory Efficiency of Symmetric Matrix
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Hash: SHA1
I'm generating a symmetric correlation matrix using a data matrix as input:
mat <- cor(data.mat)
My question is:
Is there a more memory efficient way to store this data? For instance, since:
all(mat == t(mat))
every value is duplicated, and I should be able to almost half the memory usage for large matrices.
Any thoughts/comments?
Cheers,