Anyone Familiar with Using arima function with exogenous variables?
On Mon, Apr 21, 2003 at 12:32:12PM -0400, Richard A. Bilonick wrote:
I tried using arima to estimate the sales data (Series M in Box and Jenkins) using the leading indicator. I think I estimated the same model correctly. The AR and MA coefficients roughly agreed but the intercept and coefficient for the leading indicator were very different. The intercept was 10 times too large (approximately) and the coefficient for the leading indicator was about 1/10 of that shown in B&J. So far I haven't located any simple examples to try.
Why don't you try simulation? Create some data under the 'null' you're trying to get to, say, y <- seq(1,n) + arima.error where arima.error could be as simple as an AR(1) or MA(1). Then estimate the model, using 90% or 95% of the data and evaluate the forecast to the retained 10% or 5%. Repeat the DGP creation, estimation, forecast evaluation steps N (say 500) times and you should have a good idea about the merits of predict.arima. Dirk
Don't drink and derive. Alcohol and algebra don't mix.