OK, I think I know what is the answer to this question - first I have to define a rsnns object factory, create a network (specify its architecture) and only THEN I can use train (this is what I have understood from the RSNNS manual)
However, for the sake of not being stuck with this one, I used MLPerceptron for a time being to carry on with the task of forecasting. Can someone give me a hint what is the reason for an error: Error in predict.rsnns(nn_j, forexInTest[i]) : missing values in 'x' that comes when I try to do a matrix of recursive forecasts with an mlp model? the code is below: for (j in 1:length(inputsTest)){ forexInTrain <- c(inputsTrain, inputsTest[1:j]) forexOutTrain <- c(targetsTrain, targetsTest[1:j]) nn_j<- mlp(forexInTrain, forexOutTrain, maxit=100) <- this works on a stand alone basis forexInTest <- inputsTest[j+1:length(inputsTest)] fc<-c() for (i in 1:length(forexInTest)){ fc<-c(fc,predict.rsnns(nn_j, forexInTest[i])) <-- the problem appears here } array<-(dim=c(length(inputsTest),j)) total<- as.matrix(fc) total<- cbind(total, fc) } (lengths of inputsTest=49, of inputsTrain=targetsTrain=342) cheers Sara 2011/2/27 Sara Szeremeta <sara.szerem...@gmail.com> > To provide more details: > > 1) the package I use is the RSNNS (as stated in the topic) > > 2) for input data to be split I fed in ts() object.. maybe this is a wrong > move. > Does anybody knows what is the type of object that can be fed into the > train() function from the RSNNS package? > > The input data is a matrix with two columns: the first is a 1st lag of > the second (I keep the number of inputs as simple as possible until I know > how the model works), I removed NA values, the values are lagged exchange > rates. > > The first rows look like this: > Time Series: > Start = 2 > End = 481 > Frequency = 1 > IN.1 OUT > 2 0.3855345 0.3782309 > 3 0.3782309 0.3824694 > 4 0.3824694 0.3870295 > > The split performed with the splitForTrainingAndTest(inter[,1], inter[,2], > ratio=0.10) seems good - the training and test data are appropriate. > > Then I defined: > inputsTrain<-splitForTrainingAndTest(inter[,1], inter[,2], > ratio=0.10)$inputsTrain > and so on for targets and test data. > > The train() function uses those values: nn <- train(inputsTrain, > targetsTrain,...) > > > I would greatly appreciate your help. > > > 2011/2/25 Sara Szeremeta <sara.szerem...@gmail.com> > > Hello All! >> >> I am training to train a NN with function train() after splitting data >> with the function splitForTrainingAndTest(). The split is ok (checked >> it), but when I get a try on training I get this message: >> >> Error in UseMethod("train") : >> no applicable method for 'train' applied to an object of class >> "c('double', 'numeric')" >> >> The input data are logrithms of some financial values and their first >> lags. >> >> >> Does anybody can give me a hint how to make the train() function work >> correctly? >> >> >> >> Thank you and have a good day! >> >> Sara >> >> > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.