Message-ID: <20030421162307.GA13477@sonny.eddelbuettel.com>
Date: 2003-04-21T16:23:07Z
From: Dirk Eddelbuettel
Subject: Anyone Familiar with Using arima function with exogenous variables?
In-Reply-To: <3EA41D0C.5040701@nauticom.net>
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.