Displaying 20 results from an estimated 2000 matches similar to: "qr() and Gram-Schmidt"
2003 Sep 01
1
Gram-Schmidt orthonormal factorization
Hi:
Does R have a function as gsorth is SAS, that perform a the Gram-Schmidt
orthonormal factorization of the m ?n matrix A, where m is greater than or
equal to n? That is, the GSORTH subroutine in SAS computes the
column-orthonormal m ?n matrix P and the upper triangular n ?n matrix T such
that A = P*T.
or any other version of Gram-Schmidt orthonormal factorization?
I search the help, but I
2003 Aug 13
3
A question on orthogonal basis vectors
Hey, R-listers,
I have a question about determining the orthogonal
basis vectors.
In the d-dimensinonal space, if I already know
the first r orthogonal basis vectors, should I be
able to determine the remaining d-r orthognal basis
vectors automatically?
Or the answer is not unique?
Thanks for your attention.
Fred
1999 Jun 30
1
qr and Moore-Penrose
> Date: Wed, 30 Jun 1999 11:12:24 +0200 (MET DST)
> From: Torsten Hothorn <hothorn at amadeus.statistik.uni-dortmund.de>
>
> yesterday I had a little shock using qr (or lm). having a matrix
>
> X <- cbind(1,diag(3))
> y <- 1:3
>
> the qr.coef returns one NA (because X is singular). So I computed the
> Moore-Penrose inverse of X (just from the
2012 Mar 15
6
Generation of correlated variables
Hi everyone.
Based on a dependent variable (y), I'm trying to generate some independent
variables with a specified correlation. For this there's no problems.
However, I would like that have all my "regressors" to be orthogonal (i.e.
no correlation among them.
For example,
y = x1 + x2 + x3 where the correlation between y x1 = 0.7, x2 = 0.4 and x3 =
0.8. However, x1, x2 and x3
2004 Feb 23
2
orthonormalization with weights
Hello List,
I would like to orthonormalize vectors contained in a matrix X taking into
account row weights (matrix diagonal D). ie, I want to obtain Z=XA with
t(Z)%*%D%*%Z=diag(1)
I can do the Gram-Schmidt orthogonalization with subsequent weighted
regressions. I know that in the case of uniform weights, qr can do the
trick. I wonder if there is a way to do it in the case of non uniform
2010 Jun 08
1
LumenVox *.gram reload
I just made a change to one of my *.gram files for my LumenVox IVR. I was just wondering if anyone knows the command in Asterisk to reload the .gram files.
Thanks for your help
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2010 Jul 16
3
how to skip a specific value when using apply() function to a matrix?
Hello R experts,
I'd like to studentize a matrix (tmp1) by column using apply() function and skip some specific values such as zeros in the example below to tmp2 but not tmp3. I used the script below and only can get a matrix tmp3. Could you please help me to studentize the matrix (tmp1) without changing the zeros and generate a new matrix tmp2?
Thanks,
Joshua
tmp1
[,1] [,2] [,3] [,4]
2003 Feb 14
2
How to solve A'A=S for A
It is not clear to me that one can. If the singular value decomposition
of A is the triple product P d Q', then the singular value decomposition
of A'A=S is Q d^2 Q'. The information about the orthonormal matrix P is
lost, is it not?
**********************************************************
Cliff Lunneborg, Professor Emeritus, Statistics &
Psychology, University of Washington,
2010 Jan 16
2
La.svd of a symmetric matrix
Dear R list users,
the singluar value decomposition of a symmetric matrix M is UDV^(T), where U = V.
La.svd(M) gives as output three elements: the diagonal of D and the two orthogonal matrices u and vt (which is already the transpose of v).
I noticed that the transpose of vt is not exactly u. Why is that?
thank you for your attention and your help
Stefano
AVVISO IMPORTANTE: Questo messaggio di
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
2006 Apr 18
2
typos in src/main/gram.y (PR#8780)
In src/main/gram.y, the documentation for R_ParseVector has a wrong
signature:
SEXP R_ParseVector(TextBuffer *text, int n, ParseStatus *status)
should be
SEXP R_ParseVector(SEXP text, int n, ParseStatus *status)
In addition, the two occurrences of "IOBuffer" in the documentation
should be replaced by "IoBuffer".
version.string = Version 2.3.0 beta (2006-04-14 r37779)
2006 Sep 08
2
Complete documentation gram.y ??
Hi everybody,
Does anybody know where I can find documentation about
file gram.y?. What I need to do is related to the
parse tree. I need the parse tree of a R user defined
function for being used by a c++ function. Briefly, I
have a C++ function that is used to generate random
numbers from a specified objective function and I want
to use R just to verified the sintaxis of the function
and I
2003 Jul 11
1
How to generate regression matrix with correlation matrix
Dear R community:
I want to simulate a regression matrix which is generated from an orthonormal matrix X of dimension 30*10 with different between-column pairwise correlation coefficients generated from uniform distribution U(-1,1).
Thanks in advance!
Rui
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2007 Apr 12
1
LME: internal workings of QR factorization
Hi:
I've been reading "Computational Methods for Multilevel Modeling" by Pinheiro and Bates, the idea of embedding the technique in my own c-level code. The basic idea is to rewrite the joint density in a form to mimic a single least squares problem conditional upon the variance parameters. The paper is fairly clear except that some important level of detail is missing. For
2006 Feb 22
1
Gram-Charlier series
Good day everyone,
I want to use the Gram-Charlier series expansion to model
some data. To do that, I need functions to:
1) Calculate 'n' moments from given data
2) Transform 'n' moments to 'n' central moments, or
3) Transform 'n' moments to 'n' cumulants
4) Calculate a number of Hermite polynomials
Are there R-functions to do any of the above?
More clear statement about the question of how to generate regression matrix with correlation matrix
2003 Jul 12
1
More clear statement about the question of how to generate regression matrix with correlation matrix
Dear R community:
I am trying to do a simulation study mentioned by Fu (1998), Journal of Computational and Graphical Statistics, Volume7, Number 3, Page 397-416. In order to give a clear statement of quesion I copy the following paragraph from the article: We compare the bridge model with the OLS, the lasso and the ridge in a simulation of a linear regression model of 30 observations and 10
2007 Jan 20
4
Question about converting from square roots to decimals and back
Hi,
I apologize if there is a simple answer to this question that I've
missed. I did search the mailing list but I might not have used the
right keywords. Why does sum(A3^2) give the result of 1, but
sum(A3^2)==1 give the result of FALSE?
> A3<-matrix(nrow=3,c(1/(2^.5),1/(2^.5),0))
> A3
[,1]
[1,] 0.7071068
[2,] 0.7071068
[3,] 0.0000000
> sum(A3^2)
[1] 1
>
2011 Dec 13
2
Inverse matrix using eigendecomposition
General goal: Write R code to find the inverse matrix of an nxn positive
definite symmetric matrix. Use solve() to verify your code works.
Started with a 3x3 matrix example to build the code, but something dosen't
seem to be working. I just don't know where I am going wrong.
##Example matrix I found online
A<-c(4,1,-1,1,2,1,-1,1,2)
m<-matrix(A,nrow=3,ncol=3)
##Caculate the eigen
2016 Oct 24
3
typo or stale info in qr man
man for `qr` says that the function uses LINPACK's DQRDC, while it in
fact uses DQRDC2.
```
The QR decomposition of the matrix as computed by LINPACK or LAPACK.
The components in the returned value correspond directly to the values
returned by DQRDC/DGEQP3/ZGEQP3
```
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