search for: chols

Full_Name: David Pleydell Version: 2.2.1 OS: Debian Etch Submission from: (NULL) (193.55.70.206) There appears to be a conflict between the chol functions from the Matrix and the SparseM packages. chol() can only be applied to a matrix of class dspMatrix if SparseM is not in the path. with gratitude David > library(Matrix) > sm <- as(as(Matrix(diag(5) + 1), "dsyMatrix"),

I have been running into difficulties with dispatching on an S4 class defined in the SparseM package, when the method calls are inside a function passed as the f= argument to optimize() in functions in the spdep package. The S4 methods are typically defined as: setMethod("det","matrix.csr", function(x, ...) det(chol(x))^2) that is within setMethod() rather than by name before

Hi, how can I get a more descriptive text instead of the variable names in my XY-lattice plot, according to the table below? Variable text acet = "Acetylaspartate Thalamus" chol = "Choline Thalamus" acetp = "Acetylaspartate parieoc" ino = "Inositole Thalamus" I could not find a solution. Please have a look at my syntax. Thanks a lot,

I think I am missing something with the chol() function. Here is my calculation: ? > mat ???? [,1] [,2] [,3] [,4] [,5] [1,]??? 1??? 3??? 0??? 0??? 0 [2,]??? 0??? 1??? 0??? 0??? 0 [3,]??? 0??? 0??? 1??? 0??? 0 [4,]??? 0??? 0??? 0??? 1??? 0 [5,]??? 0??? 0??? 0??? 0??? 1 > eigen(mat) $values [1] 1 1 1 1 1 $vectors ???? [,1]????????? [,2] [,3] [,4] [,5] [1,]??? 1 -1.000000e+00??? 0??? 0??? 0

Full_Name: Jerome Asselin Version: 1.3.0 OS: Windows 98 Submission from: (NULL) (24.77.112.193) I am having accuracy problems involving the computation of inverse of nonnegative definite matrices with solve(). I also have to compute the Choleski decomposition of matrices. My numerical problems involving solve() made me find a bug in the chol() function. Here is an example. #Please, load the

I am using 2.2.0 If the QR decomposition of an N*M matrix is such that the pivoting order is not 1:M, Q%*%R does not result in the original matrix but in a matrix with the columns permuted. This is clearly intentional, and probably to be expected if pivoting is used --- chol() behaves in the same manner (it would perhaps be nice if the qr help page made that clear in the same way that the chol()

Hi Everyone, I have modified my version of R-1.4.1 to include choleski with pivoting (like in Splus). I thought R-core might consider including this in the next version of R, so I give below the steps required to facilitate this. 1. Copied Linpack routine "dchdc.f" into src/appl 2. Inserted line F77_SUBROUTINE(dchdc) in src/appl/ROUTINES 3. Inserted "dchdc.f" into

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

Dear R-users: I can not reproduce figure 4 of *Statistical Tables and Plots using S and LATEX* by Prof. Frank Harrell with the following code: rm(list=ls()) library(Hmisc) getHdata(pbc) attach(pbc) age.groups <- cut2(age, c(45,60)) g <- function(y) apply(y, 2, quantile, c(.25,.5,.75)) y <- with(pbc, cbind(Chol=chol,Bili=bili)) # You can give new column names that are not legal S names

Hi Everyone, Just a minor point, but could chol() be changed to include the dimnames of the original matrix? This will ensure that x and t(R) %*% R have the same dimnames, where R <- chol(x). So we just need to insert if (!is.null(dx <- dimnames(x))) dimnames(z$v) <- dx ahead of the return. Cheers, Jonathan. Jonathan Rougier Science Laboratories

Dear all, I have following list object: dat <- vector("list", length=4) for(i in 1:4) dat[[i]] <- diag(rnorm(5)^2) names(dat) <- paste("A", 1:4, sep="") It is ok upto this point. However if I want apply, suppose chol() function on any of it's element, I am getting error: > chol(dat['A1']) Error in chol.default(dat["A1"]) :

Hi there, Given a positive definite symmetric matrix, I can use chol(x) to obtain U where U is upper triangular and x=U'U. For example, x=matrix(c(5,1,2,1,3,1,2,1,4),3,3) U=chol(x) U # [,1] [,2] [,3] #[1,] 2.236068 0.4472136 0.8944272 #[2,] 0.000000 1.6733201 0.3585686 #[3,] 0.000000 0.0000000 1.7525492 t(U)%*%U # this is exactly x Does anyone know how to obtain L such

Dear all, (sorry I got the wrong button for subscribing a minute ago) At the moment I'm writing on a package for random field simulation that I'd like to make publically availabe in near future. To this end I've asked Martin Maechler to have a look at my R-code. He was very surprised about how I perform the ".C"-calls, and encouraged me to make this request for comments.

Dear All, My question is simple but I need someone to help me out. Suppose I have a positive definite matrix A. The funtion chol() gives matrix L, such that A = L'L. The inverse of A, say A.inv, is also positive definite and can be factorized as A.inv = M'M. Then A = inverse of (A.inv) = inverse of (M'M) = (inverse of M) %*% (inverse of M)' = ((inverse of

Hi all, I'm working out some Fortran code for which I want to compute the Choleski decomposition of a covariance matrix in Fortran. I tried to do it by two methods : 1) Calling the lapack function DPOTRF. I can see the source code and check that my call is correct, but it does not compile with: system("R CMD SHLIB ~/main.f") dyn.load("~/main.so") I get: Error in

Thanks for your message! Actually it works quite well for me too. If I then take the trace of the final result below, I end up with a number made up of both a real and an imaginary part. This does not probably mean much if the trace of the matrix below givens me info about the degrees of freedom of a model... Simona >----Messaggio originale---- >Da: RVaradhan at jhmi.edu >Data:

Dear Peter, thank you very much for your answer. My problem is that I need to calculate the following quantity: solve(chol(A)%*%Y) Y is a 3*3 diagonal matrix and A is a 3*3 matrix. Unfortunately one eigenvalue of A is negative. I can anyway take the square root of A but when I multiply it by Y, the imaginary part of the square root of A is dropped, and I do not get the right answer. I tried

I've been writing some matrix-type methods for a new class of sparse matrices and for most methods this has been straightforward. However, there are examples, like %*% and chol, that (apparently) R doesn't automatically recognize as generic. What to do in these cases? At this point, I've been writing new generic methods with slightly perturbed names %m% and cholesky for example in

Hi all R users ! I'm using gamm function from Simon Wood's mgcv package, to fit a spatial regression Generalized Additive Mixed Model, as covariates I have the geographical longitude and latitude locations of indexed data. I include a random effect for each district (dist) so the code is fit <- gamm(y~s(lon,lat,bs="tp", m=2)+offset(log(exp.)), random=list(dist=~1),

Hi all, I have fitted a gee model with the gee package and included restricted cubic spline functions. Here is the model: chol.g <- gee(SKIN ~ rcs(CHOLT, 3), id=ID, data=chol, family=binomial(link="logit"), corstr="exchangeable") To extract the log odds I use: predict.glm(chol.g, type = "link") Now I want to compute the logg odds for specific CHOLT values