similar to: ga: genetic algorithms package

Dear All, Ulric Lund and me are developing a new package called 'circular' that as soon as possible will substitute 'CircStats' package. A pre-released is available at: http://www.dst.unive.it/~claudio/R/circular_0.1.tar.gz I kindly ask everybody is using CircStats to check this new package and send me comments, suggestions and bugs to claudio at unive.it and not to the list. As

Dear All, Ulric Lund and me are developing a new package called 'circular' that as soon as possible will substitute 'CircStats' package. A pre-released is available at: http://www.dst.unive.it/~claudio/R/circular_0.1.tar.gz I kindly ask everybody is using CircStats to check this new package and send me comments, suggestions and bugs to claudio at unive.it and not to the list. As

> From: Claudio Agostinelli [mailto:mail-list at linaria.dst.unive.it] > > Dear All, > I think there is a small bug in sd when the argument is a > dataframe and > there are missing values: > > > x <- data.frame(matrix(rnorm(12,0,1), nrow=4, ncol=3)) > > x[1,1] <- NA > > sd(x) > Error in var(x, na.rm = na.rm) : missing observations in cov/cor >

Hi, I installed "circular" package and I wanted to load it automatically when R starts up, so I added the following lines in file Rprofile.site, .First <- function() library(circular) When R starts up, it gives me the following error: ---------- Loading required package: boot Loading required package: graphics Loading required package: stats Error : .onAttach failed in

Hi, I am looking for genetic optimization package that allow to define my own chromosome solution and crossover/mutation opoerations. I checked genoud and genopt, not with much effort of 'cause, with no luck. Any one can shed some light on this? thanks.

mcga 1.1 (machine coded genetic algorithms) package implements a genetic algorithm optimisation tool with machine coded chromosomes. The machine coded chromosomes stand for chromosomes that are not decoded and encoded. The byte representation of 'double' type variables are crossed-over and mutated. This is different from the binary coded and real coded genetic algorithms. Linux and

mcga 1.1 (machine coded genetic algorithms) package implements a genetic algorithm optimisation tool with machine coded chromosomes. The machine coded chromosomes stand for chromosomes that are not decoded and encoded. The byte representation of 'double' type variables are crossed-over and mutated. This is different from the binary coded and real coded genetic algorithms. Linux and

Hello, I'm new to R, I have two questions: Is there some implementation og Genetic Algorithms in R? Is there a pre-dvi'd manual of R? thanks. E. Crespi. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the

Hi all. I would like to use the rbga.bin function (from the "genalg" package) as part of a model selection process to whittle down a list of ~40 potential explanatory variables to only the most important ones. Unfortunately, despite my working knowledge of R for linear modeling and basic statistics, I cannot understand the two examples provided with the documentation for rbga.bin

OK, here is some code that may be of use to someone: http://www.progsoc.uts.edu.au/~telford/samples/R/gafit_0.1.tar.gz Hopefully it might make contrib status on CRAN :-) It uses a genetic algorithm to seek the lowest value of some user-defined target function (or seeks the most negative value if negative values are possible). By using a sum of squared residuals for the target function, it

Hi, I am doing some research on feature selection for classfication problem using genetic algorithm in a wrapper approach. I am wondering if there is some package which is already built for this purpose. I was advised before about dprep package but I don't think it used GA there (if I am wrong, please correct me!) Thanks, Ed

Hi, I'm looking for a R-package that does feature selection for PLS using a genetic optimization algorithm. I couldn't find one on CRAN and I wonder whether there is a free one. I would be very appreciative for any help. Regards Rolf

We are happy to announce that the second R user conference useR! 2006 is scheduled for June 15-17 2006 and will take place at the Vienna University of Economics and Business Administration. This second world-meeting of the R user community will focus on - R as the `lingua franca' of data analysis and statistical computing, - providing a platform for R users to

We are happy to announce that the second R user conference useR! 2006 is scheduled for June 15-17 2006 and will take place at the Vienna University of Economics and Business Administration. This second world-meeting of the R user community will focus on - R as the `lingua franca' of data analysis and statistical computing, - providing a platform for R users to

Hi Everyone, I need to use genetic algorithm to find the minimum. The problem is, I cannot define the fitness function, but I can build a neural network from the input data and use the output as a fitness function. Can this be done? The other problem is, I know there are a few package in R related to GA. So far I know all of them take a specific function as fitness function, is

Hi, we have some code that does variable selection with a genetic algorithm or simulated annealing, using a linear regression routine or neural network as the objective function. This code is a mixture of fortran and C. The code is more than 15 years old and I am planning to rework it. Though a C rewrite would be good for efficiency, I would like to protoype it quickly in R and see how it

Dear List, I'm using glmulti for model averaging in R. There are ~10 variables in my model, making exhaustive screening impractical - I therefore need to use the genetic algorithm (GA) (call: method = "g"). I need to include random effects so I'm using glmulti as a wrapper for lme4. Methods for doing this are available here

Hello all, I am trying to implement a simple Genetic Algorithm. I am doing this in R since I want access to the statistical functions (eg lm) it provides. I'm not new to programming, or GAs, but I am totally new to R (the package and the language), and I am hoping someone could help with these questions: 1. I am going to use a binary representation, it seems that vectors of Factors would

Hi all, This is really a stats question as much as an R question. I'm trying to do a joint scaling test (JST - see below) on some very oddly-distributed data and was wondering if anyone can suggest a good way of dealing with model violations and/or using R to evaluate how sensitive the model is to violations of the normality assumption. Here's a quick explanation of the analysis, the

Does anyone use the R library GenABEL? I am using it to calculate SNP interactions. I have a list of 100 SNPs, I need to look at the interaction between each of two SNPs among the list. my question is how to perform this in GenABEL. I want to use the "lm" function, but don't know how to use the SNP information. for example: result <- (lm(y~SNP1+SNP2+SNP1*SNP2)) the problem here