search for: semidefinit

Displaying 20 results from an estimated 22 matches for "semidefinit".

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2012 Apr 26
0
nearest positive semidefinit toeplitz matrix
hHllo, I'm looking for an algroithm to transform an existing toeplitz matrix (autocorrelation matrix) to the nearest positive semidefinite toeplitz matrix. I merely found an algorithm to transform an correlation matrix via the function nearcor() based on the algorithm of Higham. But as I examined, it destroys the toeplitz structure of my underlying matrix. Does any function already exist in R, which deals with my problem?...
2007 Nov 14
2
convex optimization package for R, specifically semidefinite programming
Recently, a package for convex optimization was announced for Python, based upon the LP solver GLPK, the SDP solver in DSDP5, and the LP and QP solvers in MOSEK. I'm aware GLPK is available for R, but wondered if anyone had good packages for convex optimization along these lines for R. TIA.
2011 May 27
1
eigenvalues and correlation matrices
I'm trying to test if a correlation matrix is positive semidefinite. My understanding is that a matrix is positive semidefinite if it is Hermitian and all its eigenvalues are positive. The values in my correlation matrix are real and the layout means that it is symmetric. This seems to satisfy the Hermitian criterion so I figure that my real challenge is to chec...
2004 Dec 12
2
Help : generating correlation matrix with a particular structure
Hi, I would like to generate a correlation matrix with a particular structure. For example, a 3n x 3n matrix : A_(nxn) aI_(nxn) bI_(nxn) aI_(nxn) A_(nxn) cI_(nxn) aI_(nxn) cI_(nxn) A_(nxn) where - A_(nxn) is a *specified* symmetric, positive definite nxn matrix. - I_(nxn) is an identity matrix of order n - a, b, c are (any) real numbers Many attempts have been unsuccessful because a
2007 Dec 12
2
Matrix Inversion
I got the following error: a = read.csv("mat.csv") b = as.matrix(a) tb = t(b) bb = tb %*% b dim(bb) ibb = solve(bb) bb %*% ibb > ibb = solve(bb) Error in solve.default(bb) : system is computationally singular: reciprocal condition number = 1.77573e-19 > Are there any ways to find more information about why it is singular? Thanks.
2010 Dec 04
1
Quadratic programming with semi-definite matrix
...nda okay since I expect it to be numerically semi-definite in most cases. As far as I'm aware the problem arises because the Goldfarb and Idnani method first solves the unconstrained problem requiring a positive definite matrix. Are there any (fast) packages that allows me to do QP with (large) semidefinite matrices? Example: t <- 100 y <- signalConvNoisy[1,] D <- crossprod(H,H) d <- crossprod(H,y) A <- cbind(rep(-1, nrow(H)), diag(ncol(H))) b0 <- c(t, rep(0, ncol(H))) sol <- solve.QP(Dmat=D, dvec = d, Amat = A, bvec = b0)$solution Error in solve.QP(Dmat = D, dvec = d, Amat = A,...
2004 Sep 01
0
not positive definite D matrix in quadprog
...to use solve.QP, but I get an error message that matrix D in quadratic function is not positive definite. For reference, a fully R session is listed below. Is 10^(-12) too close to 0? i.e., does R consider that with an eigenvalue of order +10^(-12) the matrix is not positive definite but positive semidefinite? In general, has somebody know a way (in R or outside R, maybe in c++) to solve quadratic programming with positive semidefinite matrices? In particular, my problem is not so hard: given y an n x 1 matrix, and beta an n x m matrix, I want to find an m x 1 matrix x s. t. sum(y - beta * x)^2 i...
2004 Dec 10
1
How to circumvent negative eigenvalues in the capscale function
Dear All I am trying to do a partial canonical analysis of principal coordinates using Bray-Curtis distances. The capscale addin to R appears to be the only way of doing it, however, when I try and calculate a Bray-Curtis distance matrix either using Capscale or Vegedist (capscale I understand uses Vegedist anyway to calculate its distance matrix), R uses up all available memory on the computer,
2012 Dec 05
1
Understanding svd usage and its necessity in generalized inverse calculation
Dear R-devel: I could use some advice about matrix calculations and steps that might make for faster computation of generalized inverses. It appears in some projects there is a bottleneck at the use of svd in calculation of generalized inverses. Here's some Rprof output I need to understand. > summaryRprof("Amelia.out") $by.self self.time self.pct
2009 Dec 28
0
micEcon split into miscTools, micEconAids, and micEcon
..." package has been split into three packages: miscTools, micEconAids, and micEcon. a) miscTools (version 0.6-0) includes miscellaneous small tools and utilities that are not related to (micro)economics, e.g. colMedians(), rowMedians(), insertCol(), insertRow(), vecli(), symMatrix(), triang(), semidefiniteness(), compPlot(), and rSquared(). The miscTools package should depend on (almost) no other packages so that it can be used in other packages without increasing the total (recursive!) dependencies of these packages too much. b) micEconAids (version 0.6-0) includes all functions and methods for de...
2004 May 11
2
bilinear and non linear
Dear all, there are R packages able to simulate or estimate bilinear model for time series? I know it is an open problem, but do exist something for very simplified bilinear models? Alternatively, what kinfd of non linear time series models are performed in R? If R is not able, could someone suggest me for some commercial softwares to deal with bilinear models? i'm afraid of a negative
2005 Oct 15
1
solve() versus ginv()
Dear All, While inverting a matrix the following error appears on my console: Error in solve.default(my_matrix) : Lapack routine dgesv: system is exactly singular With this respect, I have been replacing the solve() function with ginv(): the Moore-Penrose generalized inverse of a matrix. These are the questions I would like to ask you: 1. Would you also replace solve() with ginv() in
2009 Dec 28
0
micEcon split into miscTools, micEconAids, and micEcon
..." package has been split into three packages: miscTools, micEconAids, and micEcon. a) miscTools (version 0.6-0) includes miscellaneous small tools and utilities that are not related to (micro)economics, e.g. colMedians(), rowMedians(), insertCol(), insertRow(), vecli(), symMatrix(), triang(), semidefiniteness(), compPlot(), and rSquared(). The miscTools package should depend on (almost) no other packages so that it can be used in other packages without increasing the total (recursive!) dependencies of these packages too much. b) micEconAids (version 0.6-0) includes all functions and methods for de...
2011 Apr 11
3
Coding matrix equation
Hi all, I have two matrices: G<-matrix(c(2.0, 0.5, 0.5, 0.5, 2.0, 0.5, 0.5, 0.5,2.0),3,3) P<-matrix(c(1.0, 0.5, 0.5, 0.5, 1.0, 0.5, 0.5, 0.5,1.0),3,3) and I want to run this equation to get a new matrix F: F = [P+2G]^-1/2 P [P+2G]^-1/2 Could someone please tell me how to code this in R? Many thanks in advance for your time. Best wishes, Matt [[alternative HTML version deleted]]
2004 Dec 13
1
Re: Help : generating correlation matrix with a particular
...nt > >X1 and Y1 correlated >X2 and Y2 correlated >X1 and X2 correlated >Y1 and Y2 correlated > >but > >X1 and Y2 uncorrelated >Y1 and X2 uncorrelated > > >One approach is to work out the conditional variance of (X2,Y2) given >(X1,Y1) and check for positive semidefiniteness. You do the math... > >(Some preliminary experiments suggest that the criterion could be >abs(a)+abs(r) <= 1, but don't take my word for it) > >> R-version used : >> --------------- >> Windows version >> R-1.8.1 >> Running on Windows XP > &gt...
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 -0.01619026  0.78213630 [3,] -0.8356286  0.7383247
2009 Mar 10
5
Cholesky Decomposition in R
Hi everyone: I try to use r to do the Cholesky Decomposition,which is A=LDL',so far I only found how to decomposite A in to LL' by using chol(A),the function Cholesky(A) doesnt work,any one know other command to decomposte A in to LDL' My r code is: library(Matrix) A=matrix(c(1,1,1,1,5,5,1,5,14),nrow=3) > chol(A) [,1] [,2] [,3] [1,] 1 1 1 [2,] 0 2 2
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
2005 Dec 12
2
convergence error (lme) which depends on the version of nlme (?)
Dear list members, the following hlm was constructed: hlm <- groupedData(laut ~ design | grpzugeh, data = imp.not.I) the grouped data object is located at and can be downloaded: www.anicca-vijja.de/lg/hlm_example.Rdata The following works: library(nlme) summary( fitlme <- lme(hlm) ) with output: ... AIC BIC logLik 425.3768 465.6087 -197.6884 Random effects:
2007 Jul 13
2
nearest correlation to polychoric
Dear all, Has someone implemented in R (or any other language) Knol DL, ten Berge JMF. Least-squares approximation of an improper correlation matrix by a proper one. Psychometrika, 1989, 54, 53-61. or any other similar algorithm? Best regards Jens Oehlschl?gel Background: I want to factanal() matrices of polychoric correlations which have negative eigenvalue. I coded Highham 2002