I am new to R and the ARIMA model and I am attemping to forecast 1440 values into the future using a base of roughly 5000 numbers. It is data extracted roughly every minute from a machine log(performance values). The intend to forecast 1 day into the future, which explains the 1440 values(as they are minutes).
Here is my result using the following commands: datats<-c(data); arima<-auto.arima(datats); fcast<-forecast(arima, h=1440);
The prediction begins at the flat line on the right hand side.
Forecast method: ARIMA(0,1,1)
Model Information: Series: datats ARIMA(0,1,1)
Coefficients: ma1 -0.9373 s.e. 0.0071
sigma^2 estimated as 86737: log likelihood=-21221.46 AIC=42446.93 AICc=42446.93 BIC=42458.93
Error measures: ME RMSE MAE MPE MAPE MASE Training set 0.6506441 294.4619 196.7211 -59.85254 85.45473 0.7637028 ACF1 Training set 0.01519673
Dataset here: http://pastebin.com/92ssDExn
Is the issue too little past values? To many values to be predicted?
Any information or advice would be extremely welcomed, any other information required will be provided.