similar to: forecast: bias in sampling from seasonal Arima model?

I have a data file with a given time series of price data and I would like to split the time series into a test set and training set. I would then like to build an ARIMA model on the training set and apply this model on test set. Below is some code: [CODE] data= read.table("A.txt",sep=",") attach(data) training = data[1:120, 6] test = data[121:245, 6] ts1 = ts(training) ts2 =

arima1 = arima(data.ts[1:200], order = c(1,1,1)) arima2 = arima(data.ts[5:205], order = c(1,1,1)) arima3 = arima(data.ts[10:210], order = c(1,1,1)) arima4 = arima(data.ts[15:215], order = c(1,1,1)) arima5 = arima(data.ts[20:220], order = c(1,1,1)) arima6 = arima(data.ts[25:225], order = c(1,1,1)) arima7 = arima(data.ts[30:230], order = c(1,1,1)) arima8 = arima(data.ts[35:235], order = c(1,1,1))

Hi. I hope you can help me... I have fitted the following ARIMA model: arima1<-arima(bigspring$log.volume, order=c(0,1,2)) I need to predict 30 days ahead. I used following code predict(arima1,n.ahead=30,se=T) However I get 30 predictions, but from predictions 2:30 I get the same predictions. Why is this? What am I doing wrong Thanks Catherine KSS Ltd Seventh Floor St

I have been trying to simulate from a time series with trend but I don't see how to include the trend in the arima.sim() call. The following code illustrates the problem: # Begin demonstration program x <- c(0.168766559, 0.186874000, 0.156710548, 0.151809531, 0.144638812, 0.142106888, 0.140961714, 0.134054659, 0.138722419, 0.134037018, 0.122829846, 0.120188714,

Hello R people, I am need some help using the try() function. Currently I am running a loop which uses arima() for some values of p and q, which sometimes crashes. When it crashes, I want the program to just ignore it and move on to the next values to loop through. I currently have this, looping through a range of values for p and q: lo = try( arima1 <- arima( y, order=c( p, 0, q ) ) if(

sseq <- c(1, seq(5, 120, by = 5)) for(i in 1:length(sseq)){ assign(paste("arima", i, sep=""), arima0(data.ts[sseq[i]:(sseq[i]+115)], order=c(1,1,1))) } pred1 = predict(arima1, n.ahead = 5, se.fit = TRUE)$pred how do I traverse the arima models so I repeat the above prediction procedure(bold) on all arima models. Also, how do i automatically create one huge vector of the

I have a question about pooling or "stacking" several time series ?samples? (sorry in advance for the long, possibly confusing, message). I'm sure I'm revealing far more ignorance than I'm aware of, but that's why I'm sending this... [Example at bottom] I have regional migration flows (?samples?) from, say, regions A to B, A to C, B to A, ?., C to B (Noted as