Re: [R] R time series analysis

2010-09-07 Thread David Winsemius
On Sep 7, 2010, at 9:33 PM, David Winsemius wrote: On Sep 7, 2010, at 7:51 PM, lord12 wrote: For each arima model, can you output an associated confidence interval for the predicted value at each time point? ?arima0 arima0 will return "... a list with components "pred", the predicti

Re: [R] R time series analysis

2010-09-07 Thread David Winsemius
On Sep 7, 2010, at 7:51 PM, lord12 wrote: For each arima model, can you output an associated confidence interval for the predicted value at each time point? ?arima0 arima0 will return "... a list with components "pred", the predictions, and "se", the estimated standard errors" as time

Re: [R] R time series analysis

2010-09-07 Thread lord12
For each arima model, can you output an associated confidence interval for the predicted value at each time point? -- View this message in context: http://r.789695.n4.nabble.com/R-time-series-analysis-tp2527513p2530595.html Sent from the R help mailing list archive at Nabble.com. _

Re: [R] R time series analysis

2010-09-06 Thread matteodefelice
lord12 wrote: > > 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. > I had recently the same problem and, a

Re: [R] R time series analysis

2010-09-05 Thread Johnson, Cedrick W.
You also may want to look at auto.arima in the 'forecast' package, which will return the "best" ARIMA model based on AIC/AICc/BIC values ?auto.arima hth c On 09/05/2010 06:02 PM, Stephan Kolassa wrote: Hi, basically, you know 5 periods later. If you use a good error measure, that is. I a

Re: [R] R time series analysis

2010-09-05 Thread Stephan Kolassa
Hi, basically, you know 5 periods later. If you use a good error measure, that is. I am a big believer in AIC for model selection. I believe that arima() also gives you the AIC of a fitted model, or try AIC(arima1). Other ideas include keeping a holdout sample or some such. I'd recommend l

Re: [R] R time series analysis

2010-09-05 Thread lord12
How do you evaluate the predictive models? For example if I have: arima1 = arima(training, order = c(1,1,1)) arima2 = arima(training, order = c(0,0,0)) x.fore = predict(arima1, n.ahead=5) x.fore1 = predict(arima2, n.ahead = 5) How do I know which arima model is better for prediction? -- View

Re: [R] R time series analysis

2010-09-05 Thread lord12
I want to also choose the post optimal parameters in the order argument. How could I easily do this? -- View this message in context: http://r.789695.n4.nabble.com/R-time-series-analysis-tp2527513p2527660.html Sent from the R help mailing list archive at Nabble.com. ___

Re: [R] R time series analysis

2010-09-05 Thread Pete B
1. try the predict function e.g. predict(arima1, n.ahead=10) 2. try the resid function e.g. resid(arima1) HTH Pete -- View this message in context: http://r.789695.n4.nabble.com/R-time-series-analysis-tp2527513p2527625.html Sent from the R help mailing list archive at Nabble.com. ___

[R] R time series analysis

2010-09-05 Thread lord12
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(

Re: [R] R time series analysis

2010-09-05 Thread lord12
How do I get the predicted values and the errors for each arima model? -- View this message in context: http://r.789695.n4.nabble.com/R-time-series-analysis-tp2527513p2527533.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-