similar to: Constraint Optimization with constrOptim

Hi volks, i have a question about the step() fkt. Is there a possibility to save the last model generated from this method. I have a loop and so i generate 100 different models with the step fkt and i want to know which model is the most common. CODE: ... missStep -> numeric(100) for (j in 1:100) { trainindex <- sample(c(1:462),300) train <- data[trainindex,] test <-

Hello at all, working with a dataset I try to optimize a non-linear function with constraint. test<-read.csv2("C:/Users/Herb/Desktop/Opti/NORM.csv") fkt<- function(x){ a<-c(0) s<-c(0) #Minimizing square error for(j in 1:107){ s<-(test[j,2] - (x[1] * test[j,3]) - (x[2] * test[j,4]) - (x[3]*test[j,5]) - (x[4]*test[j,6]) - (x[5]*test[j,7]))^2 a<- a+s} a<-as.double(a)

Dear All I have a constrained optimisation problem, I want to maximise the following function t(weights) %*% CovarianceMatrix %*% weights for the weights, subject to constraints on each element within the weights & the weights vector summing to 1. i.e. weights = (x1, x2, x3), where x1 is within some given range (a +b, a - b). I have tried to do this using the optim function in R,

Hello, in marketing-science field i do some clusteranalysis and get the experience that the scale cause the results dramatic! What recommendation can somebody give me, when i use nominal-variables(recode to 0/1 variables) with 6 point ordinal-variables. Is it better toDo a z-transformation with the ordinal variables , or should i recode this values in 0/1 binaries, too! P.S. Which is a good

Hi, At present, i have two distinct and real values for the coefficient, which is  required in AR(2) model. Based on my revision, for distinct and real values of the coefficients in AR(2) model, the correlation structure separated by lag h can be computed by p(h) = a*z1^(-h) + b*z2^(h), where p(h) is the autocorrelation separated by lag h, a and b can be determined by initial values, z1 and z2

Hi Abby, Thanks a lot for your paraphrasing and your suggestion! The problem of wrapping the list into a S3/S4 object, i.e. subclassing array or matrix, is that one also has to define a bunch of methods for subsetting, joining, etc, in order to make it behave like a list array. The reason is that most R functions for subsetting, joining, etc. do not preserve class attributes of the input, which

I am trying to maximise a complicated loglikelihood function with the "optim" command. Is there some way to get to know the estiamtes at each iteration? When I put "control=list(trace=TRUE)" as an option in "optim", I just got the initial and final values of the loglikelihood, number of iterations and whether the routine has converged or not. I need to know the

Hello list. I'm trying to rebuild the 2.6.9.67.0.20.EL kernel, but it fails even without modifications. How did I try it? Created a (non-root) build environment (not a mock ) Installed the kernel.scr.rpm and did a rpmbuild -ba --target=`uname -m` kernel-2.6.spec 2> prep-err.log | tee prep-out.log The build failed at the end: Processing files: kernel-xenU-devel-2.6.9-67.0.20.EL Checking