similar to: An example of very slow computation

Hi, I'm trying to find the maximum (likelihood) of a function. Therefore, I'm trying to minimize the negative likelihood function: # params: vector containing values of mu and sigma # params[1] - mu, params[2]- sigma # dat: matrix of data pairs y_i and s_i # dat[,1] - column of y_i , dat[,2] column of s_i negll <- function(params,dat,constant=0) { for(i in 1:length(dat[,1])) {

Dear R-Users, I am trying to use mle() to optimize two (or more) parameters, but I want to specify those parmeters in a data frame rather than having to spell them out separately in the "start" variable of mle(). My call is > mle(negll, start=list(aps=init), fixed=list(measphot=newphot, formod=formod, Nbands=Nbands), method="BFGS") where negll is a function I have

Martyn, No, that didn't work. One other thing in the mix (which I don't think is the issue) is that I call one of the C-entry points of expm. So the DESCRIPTION file imports expm, the NAMESPACE file imports expm, and the init.c file is #include "R.h" #include "R_ext/Rdynload.h" /* Interface to expm package. */ typedef enum {Ward_2, Ward_1, Ward_buggy_octave}

Martin, I am aware of --vanilla; I use it myself for some testing. In this case R_LIBS_USER was set externally (part of my login) and does not involve any of the R scripts. That means it is inherited by any subprocess. For example: tmt1495% R --vanilla --no-environ R version 3.3.1 (2016-06-21) -- "Bug in Your Hair" Copyright (C) 2016 The R Foundation for Statistical Computing

hi, i'm looking at how icecast runs on a machine... And, i find something which seems to be unusual... In fact, i just wanted to see how much ressources Icecast2 takes when number of clients changes. I fand that memory (swap, RAM)and cpu'loading is all the same whatever number of clients ???is it normal?? <p>max ___________________________________________________________ Do You

Hi, My name is Laura. I'm a PhD student at Queen's University Belfast and have just started learning R. I was wondering if somebody could help me to see where I am going wrong in my code for estimating the parameters [mu1, mu2, lambda1] of a 2-phase Coxian Distribution. cox2.lik<-function(theta, y){ mu1<-theta[1] mu2<-theta[2] lambda1<-theta[3]

I have a local library which depends on the expm library. The expm library is loaded into my personal space and I have the environment variable R_LIBS_USER set appropriately. The command "library(expm)" works just fine from the command line, and in fact the package works if I do the source() and dyn.load() commands by hand. The following sequence works: tmt% R CMD build

Hi Could anybody give me a bit of advice on some code I'm having trouble with? I've been trying to calculate the loglikelihood of a function iterated over a data of time values and I seem to be experiencing difficulty when I use the function expm(). Here's an example of what I am trying to do y<-c(5,10) #vector of 2 survival times p<-Matrix(c(1,0),1,2) #1x2 matrix

Can the expm function be used to calculate the exponential of a matrix where the matrix is multiplied by a vector in a data frame? For example for (i in 1:length(y)){ expmN<-expm(Q*y[i]) Q<-Matrix(c(1, 2, 3, 4), 2, 2) return(expmN) } Sorry I am new to R and I have been finding it difficult to get information on calculating Matrix exponentials in R. Many thanks in

Suppose I have a square matrix P P <- matrix(c(.3,.7, .7, .3), ncol=2) I know that > P * P Returns the element by element product, whereas > P%*%P Returns the matrix product. Now, P^2 also returns the element by element product. But, is there a slick way to write P %*% P %*% P Obviously, P^3 does not return the result I expect. Thanks, Harold [[alternative HTML version

Dear helpers, I am using R version 2.5.1 to estimate a multinomial logit model using my own maximum likelihood function (I work with share data and the default function of R cannot deal with that). However, the computer (I have an Athlon XP 3200+ with 512 GB ram) takes quite a while to estimate the model. With 3 categories, 5 explanatory variables and roughly 5000 observations it takes 2-3 min.

Dear list, I?m trying to register Fortran routines in randtoolbox (in srt/init.c file), see https://r-forge.r-project.org/scm/viewvc.php/pkg/randtoolbox/src/init.c?view=markup&root=rmetrics. Reading https://cran.r-project.org/doc/manuals/r-release/R-exts.html#Registering-native-routines and looking at what is done in stats package, I first thought that the following code will do the job:

Hi, Is there a function for raising a matrix to a power? For example if you like to compute A%*%A%*%A, is there an abbreviation similar to A^3? Atte Tenkanen > A=rbind(c(1,1),c(-1,-2)) > A [,1] [,2] [1,] 1 1 [2,] -1 -2 > A^3 [,1] [,2] [1,] 1 1 [2,] -1 -8 But: > A%*%A%*%A [,1] [,2] [1,] 1 2 [2,] -2 -5

Dear Davis, Thank you a lot for sharing this, and I am happy that I was not the only one who need to do it once to learn:) I proposed to add my repo to the manual. I think it makes sense to add both of ours, if possible, or we could merge them together and add that to the manual. Long-term URL stability is apparently an issue, but I think we may find a solution there. Anyway, thanks a lot for

Hi, I have a transition matrix T for which I want to find the steady state matrix for. This could be approximated by taking T^n , for large n. T= [ 0.8797 0.0382 0.0527 0.0008 0.0212 0.8002 0.0041 0.0143 0.0981 0.0273 0.8802 0.0527 0.0010 0.1343 0.0630 0.9322] According to a text book I have T^200 should have reached the steady state L L

Dear R users, When running the program below I receive the following error message: fit <- optim(parm, objective, yt = tyield, hessian = TRUE) Error in as.vector(data) : no method for coercing this S4 class to a vector I can't figure out what the problem is exactly. I imagine that it has something to do with "tyield" being a matrix. Any help on explaining what's going on

I use the very nice expm functions available from the expm and Matrix packages. My understanding is that for large sparse matrices the currently best methods available are Krylov subspace methods, but they are as far as I can tell not implemented in either of the packages mentioned, nor in any other R package I have found. Does anybody know if Krylov subspace methods are available from any R

It works! But Once I have the square root of this matrix, how do I convert it to a real (not imaginary) matrix which has the same property? Is that possible? Best, Simon >----Messaggio originale---- >Da: p.dalgaard at biostat.ku.dk >Data: 21-nov-2009 18.56 >A: "Charles C. Berry"<cberry at tajo.ucsd.edu> >Cc: "simona.racioppi at

Hi all I recently started to write a matrix exponentiation operator for R (by adding a new operator definition to names.c, and adding the following code to arrays.c). It is not finished yet, but I would like to solicit some comments, as there are a few areas of R's internals that I am still feeling my way around. Firstly: 1) Would there be interest in adding a new operator %^% that performs

Is the matrix exponential available in some package? The cannonical reference is "Nineteen dubious ways to take the exponential of a matrix". (Love that title) Terry T.