Hi Rolf,
Thanks for the response. I have re-phrased the problem. Hope this will help.
We're working on a project where our model tries to predict the value of
bookings as a time series of past bookings as well as some external flags.
The data was found to be stationary using the Dicky-Fuller test.
We have only a non-seasonal component for the AR and MA terms (small p & q
only).
No differencing was done.
Then, we used values of p = 1, 7, 8 and q = 1, 7.
The main issue is that the p values are additive and q values are
multiplicative.
We need to understand how we can implement this in Revo R.
Just to add, since we have external flags , we cannot make use of SARIMA
function.
Please let me know if any other questions.
Thank you in advance!
Regards,
Anindita Chattopadhyay | +919886800606 | www.mu-sigma.com |
-Original Message-
From: Rolf Turner [mailto:r.tur...@auckland.ac.nz]
Sent: Saturday, October 26, 2013 1:56 AM
To: Anindita Chattopadhyay
Cc: r-help@r-project.org; Harish K
Subject: Re: [R] Revo R for Arima Implementation
Your question is pretty well totally opaque to me. Describe the model you want
to fit in mathematical terms, rather than referring to The Package That Must
Not Be Named. This is the ***R*** list.
It is possible that you might want to make use of the "seasonal"
argument to the
arima() function.
cheers,
Rolf Turner
On 10/26/13 01:19, Anindita Chattopadhyay wrote:
> Hello There,
>
> We have used ARIMA(multiplicative MA and additive AR) model in SAS to come to
> our results. Please let me know how could that be implemented in R.
>
> Like, In SAS we can pass the variable as AR= (1,7) and MA=(1)(7) which is
> additive and multiplicative respectively.
>
> In R we have the option as : order = c(0, 0, 0) which is (p,d,q).Is there any
> specific way/code such that we specify the additive AR and multiplicative MA
> simultaneously?
>
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