similar to: Problem with RGenoud

Dear R user fellows, I would like to ask you about the package 'rgenoud' which is a genetic optimization tool. I ran the function 'genoud' with two variables to be minimized by the following command. result<-genoud(fn,nvars=2,starting.values=c(0.5,0), pop.size=1000, max.generations=10, wait.generations=3) Then, I had the following error message. Error in

Dear All I am using rgenoud to solve the following maximization problem: myfunc <- function(x) { x1 <- x[1] x2 <- x[2] if (x1^2+x2^2 > 1) return(-9999999) else x1+x2 } genoud(myfunc, nvars=2, Domains=rbind(c(0,1),c(0,1)),max=TRUE,boundary.enforcement=2,solution.tolerance=0.000001) How can one increase the precision of the solution $par [1] 0.7072442 0.7069694 ? I

Dear everyone, I am trying to run rgenoud on several chips simultaneusly. I used the instructions provided on Jasjeet Sekhon's Homepage (http://sekhon.berkeley.edu/rgenoud/multiple_cpus.html). However, I have the newer version of R (R 2.12) installed - for a 64-bit machine. So, when I tried to install the special version of "snow" from a zip file provided by Jasjeet on his page, R

I have been using the rgenoud package for a nonlinear least-squares problem with lots of local minima, and it works very well but takes lots of time. According to the article refrenced in the documentation, the original GENOUD-software by the same authors seems to allow for user-supplied analytical derivatives instead of numerical approximations, which would probably save some time. Does anybody

Dear R group, since I do only have a moderately fast MacBook and I would like to get my results faster than within 72h per run ( :-((( ), I tried Amazon AWS, which offers pretty fast computers via remote access. I don't want to post any code because its several hundreds lines of code, I am not looking for the "optimal" answer, but maybe some suggestions from you if faced similar

Hello - and sorry for a possibly stupid question, I'm just starting to learn rgenoud. I am defining a function with 5 parameters (p1, p2, p3, p4a, and p4b) and then want to optimize it using genoud. But I am doing something wrong. Before genoud is even able to run it says: "Error in p2 + 1.2 : 'p2' is missing". I assume I did not specify it right. My code is below. The task

Dear group, does anybody know how to export libraries/functions to all nodes when launching snow? I want to use a function from fBasics (dstable) for a rGenoud optimization routine, but I fail "making the function accessible" to the nodes created. I know how it works for variables, I know how it works in snowfall(which cant be used in that case), but I dont know how it culd work in

Dear All,   I could use a bit of help here, this function is hard to figure out (for me at least) I have the following so far:   PKindex<-data.frame(Subject=c(1),time=c(1,2,3,4,6,10,12),conc=c(32,28,25,22,18,14,11)) Dose<-200 Tinf <-0.5   defun<- function(time, y, parms) {  dCpdt <- -parms["kel"] * y[1]  list(dCpdt)  } modfun <- function(time,kel, Vd) {   out <-

I would like to limit the significant figures of the calibrated parameters determined by genoud() in the Rgenoud package. Below is some example output, where column 1 is model run number, columns 2-7 are the parameter values, and columns 8-12 are model fit statistics. I would like genoud to internally limit parameters to 4 decimal places as shown in this output. It is clear that the function is

I am trying to use rgenoud and snow with an external model and file I/O. Unlike the typical application of rgenoud and snow, I need to run an external executable and do pre- and post-processing of input and output files for each parameter set generated by genoud(). I'm hoping that someone can suggest improvements to my approach and a work-around for file I/O problems I've encountered when

Dear All,   Currently I am running the following code:   library(stats4) library(odesolve) library(rgenoud) Input<-data.frame(SUB=c(1),time=c(0.5,3,10,15),lev=c(2.05,12.08,9.02,8)) XD<-500 IT<-3 diffeqfun<-function(time, y, parms) {   if(time<=IT)      dCpdt <- (XD/IT)/parms["Vol"] -

Hi, Using R 2.15.1 on Windows 7. Have installed both versions 32 and 64bit. In both of them among others I have installed a package rgenoud When I open R gui of 32bit and write library(rgenoud) it responds by showing a functional rgenoud version 5.7-8. The same it does on Rgui 64bit. Now I am working in cygwin (v. 1.12.4.0) with xwin. Normally before when I had installed a package, I only had

I am attempting to install a anchoring vingettes package for R and I seem to have a problem with unzipping the files in R. I use the command that can be found here <http://wand.stanford.edu/anchors/>. Here is the dialog I get after entering the command: > install.packages("anchors", dependencies = TRUE, +

I installed R-2.1.0 from source on a Linux box running Red Hat Enterprise Linux WS release 4 but install.packages() wouldn't work (see below). When I install R-2.0.1 from RPM on the same system, everything is fine. Version 2.1.0 (2005-04-18), ISBN 3-900051-07-0 . . . > options(CRAN = "http://cran.fhcrc.org/") > install.packages("rgenoud") --- Please select a CRAN

Dear Friends, I have been trying to learn how to use the derivative free optimization algorithms implemented in the package RGENOUD by Mebane and Sekhon. However, it does not seem to work for reasons best described as my total ignorance. If anybody has experience using this package, it would be really helpful if you can point out where I'm making a mistake. Thanks in advance Anup Sample

We've added a column at http://cran.r-project.org/web/checks/check_summary.html of test results using the Sun Studio compiler: it is intended that these will be updated weekly. The Sun Studio compiler is that used on Solaris: these runs were on the Linux version. All the other platforms are using gcc 4, so this provides an opportunity for checking for use of gcc-specific features and

Hi R users, "genoud" function of "rgenoud" package will optimize my function. If opt = genoud(fn,2,max=TRUE,starting.value=c(1,10),........) opt$value will give the optimized value of the function, "fn". My problem is from the same opt, can I get the value of the function at the initial parameter values? I need the initial value of the function for

Hello everybody, I have a problem that is bothering me for quite a while now and I don't know the answer... I want to create global variables (out of a function) which I can access from all other functions... But somehow that does not work too well. Attached some code for an example: function_called <- function (){ result = globalvariable*globalvariable print(result) }

Hello! I have 2 variables - predictor "pred" and response variable "DV": pred<-c(439635.053, 222925.718, 668434.755, 194242.330, 5786.321, 115537.344, 100835.368, 7133.206, 159058.286, 4079991.629, 3380078.060, 2661279.136, 2698324.478, 1245213.965, 1901815.503, 1517019.451, 1396857.736, 1034030.988, 432249.574, 342329.325, 1831335.792, 2209578.859, 1641709.754,

I am trying to use the optimizing function genoud() with the snow package on a couple of i686 machines running Redhat Linux WS4 . I don't know anything about PVM or MPI, so I just followed the directions in snow and rgenoud for the simplest method and started a socket cluster. My function fn for genoud involves updating an input file for a separate numerical model with the latest parameter