similar to: How to fix error in the package 'rgenoud'

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

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've been using RGenoud for a while and it worked smoothly so far. However I came across a strange problem lately (for me at least...). It fails after the first individual and I get the following error message when I set MemoryMatrix = FALSE : Error in genoud(fn, nvars = 8, max = TRUE, pop.size = 10, : REAL() can only be applied to a 'numeric', not a 'character' when I

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

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

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

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

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

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

Dear Fellows, I would like to know how to uncompress a gz file at the R console. I could not find out any help from the R-help archive. Thanks for your great help. Best Regards, Wonsang You ----- -- Wonsang You Special Lab Non-Invasive Brain Imaging Leibniz Institute for Neurobiology http://www.ifn-magdeburg.de -- View this message in context:

Dear R Helpers, I have attempted "optim" function to solve a two-dimensional optimization problem. It took around 25 second to complete the procedure. However, I want to reduce the computation time: less than 7 second. Is there any optimization function in R which is very rapid? Best Regards, Wonsang ----- Wonsang You Leibniz Institute for Neurobiology -- View this message in

Dear fellows, I am a novice in R. I would like to combine a matrix and a vector. Assume that we have the matrix a and the vector b with same length of column. a<-matrix(seq(1:10),nrow=2,ncol=5,byrow=TRUE) a= 1 2 3 4 5 6 7 8 9 10 b<-t(c(11,12,13,14,15)) b= 11 12 13 14 15 Then, I want to combine a and b as follows. c= 1 2 3 4 5 6 7 8 9

Hello, After getting help to solve part of my problem and some delay on my part, I am posting a more refined version to see if someone can help me further. I am trying to autocalibrate a model in my subject area using the snow and rgenoud packages. I want to use the key function "fn" that is called by genoud() to finalize input, run the model executable, and compute the objective

Hi; I have a R script that includes a call to genoud(); genoud process lasts about 4 seconds, what would be OK if I hadn't have to call it about 2000 times. This yields about 2 hours of processing. And I would like to use this script operationally; so that it should be run twice a day. It seems to me that the parallel processing option included in genoud() divides the task inside the function

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

Hi, R-Helpers, I would like to ask about multiple graphs in one figure. I tried to execute the following codes. xlim <- c(1,100) ylim <- c(1,4) plot(NA, xlim=xlim, ylim=ylim) > x <- c(1:100) for(j in seq(1,10,by=1)) { y <- j*x^2+log(j) lines(x, y) } In the above codes, I had to arbitrarily set up the coordinate range of the figure in advance before

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

Hello R users, I am trying to minimize two functions with genoud. It is actually one function with two sets of data, each of them having two unknown variables (called Vcmax and gi) which have the same value in each of the function. They are called f.1 and f.2 in the code below. My objective to minimize the functions in order to get the two variables equal in each of the functions. Furthermore, I

Dear R-Helpers, I want to try the 2D (two-dimensional) convolution in R. For example, let us we have the following kernel and data. kernel <- (1,2,3,2,1) data <- array(1:100, dim=c(10,10)) I know the function 'convolve' only for one-dimensional convolution, but it is just for a 1D sequence. Is there any function for 2D convolution? For theory, please refer to the following link:

Dear all, Is there any generic algorithm code for optimization implemented in R? I searched without success. Thanks, -- Zhu Wang Statistical Science Department Southern Methodist University Phone: (214)768-2453 Fax: (214)768-4035 Email: zhuw at mail.smu.edu