similar to: About LU decomposition in R

Dear all, I just know how to solve an eaquation by using optim() or nlm(). But, now, I have three nonlinear equations, how could we use optim() or nlm() to solve  a system of nonlinear equations in R?  Thank you so much. Sincerely, Joe ___________________________________________________ 您的生活即時通 － 溝通、娛樂、生活、工作一次搞定！ [[alternative HTML version deleted]]

I've created some Splus code for a microarray problem that - needed to be in C, to take advantage of some sparse matrix properties - uses a cholesky decompostion as part of the computation For the cholesky, I used the cholesky2 routine, which is a part of the survival library. It does just what I want and I'm familiar with it (after all, I wrote it). In Splus, this all works

Dear R People: Could someone recommend a good c/c++ code (or Fortran) for LU decomposition, please? Sorry to bother about this. I'm trying to do some "non-R" work that requires a matrix inversion. Thanks, Erin -- Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto: erinm.hodgess at gmail.com

I get the following error from one of my Rd files in R CMD check (R 2-14.0) * checking Rd files ... WARNING Error in switch(attr(block, "Rd_tag"), TEXT = if (!grepl("^[[:space:]]* $", : EXPR must be a length 1 vector problem found in ?backsolve.Rd? This is likely something that will be glaringly obvious once it's pointed out, but without a line number I can't

Can we do Cholesky Decompositon in R for any matrix --------------------------------- [[alternative HTML version deleted]]

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

I specifically need rq matrix decomposition (and not qr). Looking at netlib site for LAPACK it does provide rq whereas LINPACK not. Looking at companion qr in R I see how in base it wraps with a .Call but I do not have success in doing that for a similar .Call for rq. Anyone done this or can provide matrix rewrites that allow me to do the rq decomposition with existing R funcs? Regards MJ

Hello, we have set up e164.lu as a test zone, as the delegation for 2.5.3.e164.arpa hasn't been completed yet. For all those who want to call the numbers currently availble directly via SIP, please use the zone name in your enum.conf. If you decide to use the zone, please tell me at mstorck@luxadmin.org, so as soon as the 2.5.3.e164.arpa zone is ready, I will mail you, so you may disable

Dear R-helpers, I have a question regarding LU-decomposition with function lu in package Matrix. The following simple example confuses me: Why is as.matrix(elu$U) not an upper triangular matrix? u3 <- matrix(c(1,1,1,1,1,1,-1,1,0,0,0,0,0,-1,1,0,0,0,-1,0,1,0,0,0,0,0,-1,1,0,0),5,6,byrow=T) elu <- expand(lu(Matrix(u3,sparse=F))) as.matrix(elu$U) I only have very limited experience with the

Hy all, recently I upgraded to S10U8 a T5120 using LU. The system had a zones configured and at time of upgrade procedure the zones was still alive and worked fine. The LU procedure was ended successfully. Zones on the system was installed in a ZFS filesystem. Here the result at the end of LU (ABE-from: s10Aug2007, ABE-to: s10Set2009): # zfs list NAME USED AVAIL REFER MOUNTPOINT

There is a bug in Matrix package, please check it, thanks! Matlab result: x = 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 >> lu(x) ans = 21.0000 22.0000 23.0000 24.0000 25.0000 0.0476 0.9524 1.9048 2.8571 3.8095 0.7619

Hey, All In principal component analysis (PCA), we want to know how many percentage the first principal component explain the total variances among the data. Assume the data matrix X is zero-meaned, and I used the following procedures: C = covriance(X) %% calculate the covariance matrix; [EVector,EValues]=eig(C) %% L = diag(EValues) %%L is a column vector with eigenvalues as the elements percent

Hello Everyone I have a MCMC loop to calculate a time varying hierarchical Bayesian structure. This requires me to use around 5-6 matrix inversions in the loop. I use cholesky and chol2inv for the matrix decomposition. Because of the data I am working with I am required to invert a 167 by 167 matrix twice in one iteration. I need to run the iteration for 10000 times, but I get the error

I was playing around a bit to see how I could find the two points in a set of points (or ordered pairs) furthest from each other. Here's what I did: 1) created a Nrow by 2col matrix, so each row contains an x,y coordinate pair. 2) fed the matrix to a nested mapply (cv is my matrix): mapply(function(k,l) mapply(function(x,y,a,b) +

Hi All, I'm still pretty new to using R - and I was hoping I might be able to get some advice as to how to use 'apply' or a similar function instead of using nested for loops. Right now I have a script which uses nested for loops similar to this: i <- 1 for(a in Alpha) { for (b in Beta) { for (c in Gamma) { for (d in Delta) { for (e in Epsilon) { Output[i] <-

Dear all, I am running glmer() in R. How can I retrieve the estimates of fixed effects and the variance of the random effects from the result? Thank you so much. Joe ___________________________________________________ ±zªº¥Í¬¡§Y®É³q ¡Ð ·¾³q¡B®T¼Ö¡B¥Í¬¡¡B¤u§@¤@¦¸·d©w¡I [[alternative HTML version deleted]]

Dear all R-users, When I install the package "lme4" in R-2.11.1, and use it to run the simulation on the Linux system, it appears the following problem. Attaching package: 'lme4' The following object(s) are masked from 'package:stats':     AIC Error in names(argNew)[1] <- names(formals(new))[[1]] :   replacement has length zero Calls: initial ... lmerFactorList

Is there any implementation in R for finding the phase shift between two continuous signals. I would like to find the average phase shift for tow signals over two years. thanks Stephen -- Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are mammals, and have not exhausted

greetings, i'm trying plot() from Owen's _The R Guide_ and having trouble with being able to view the result. the Graphics Device 2 draws an image i can only see the top part of and when i try to manipulate the window to see the image, the window then says: "...ure margins too lar..." in large letters. i guess it says something about picture margins too large. i'm not sure

Hi there, Please help me this out. > m [,1] [,2] [1,] 1.1 1.0 [2,] 1.0 1.1 > chol2inv(m) [,1] [,2] [1,] 1.5094597 -0.7513148 [2,] -0.7513148 0.8264463 > CT -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or