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Date:   Wed, 9 Mar 2011 12:27:35 -0300
Reply-To:   Ricardo Gonçalves da Silva <rgs.rsilva@BANCOVOTORANTIM.COM.BR>
Sender:   "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:   Ricardo Gonçalves da Silva <rgs.rsilva@BANCOVOTORANTIM.COM.BR>
Subject:   RES: FORECAST-- help
Comments:   To: Pradeep <chittiprolupradeep@GMAIL.COM>
In-Reply-To:   <AANLkTi=YSG=kOb34YOEG3tH+v-ODXHCuJR1Zik9-d16T@mail.gmail.com>
Content-Type:   text/plain; charset="iso-8859-1"

Hi,

Your main problem is the number of points you have to estimate the regression. Given the natural dependence structure of a time series, 12 points to forecast 12 more, is a very small sample. You can try to use some kind of bootstrap technique. In SAS, I believe you will need to implement it, but in R there's a package (BootPR), which does this.

Rick

-----Mensagem original----- De: SAS(r) Discussion [mailto:SAS-L@LISTSERV.UGA.EDU] Em nome de Pradeep Enviada em: terça-feira, 8 de março de 2011 03:32 Para: SAS-L@LISTSERV.UGA.EDU Assunto: Re: FORECAST-- help

I tried with exponential smoothing and arima both and by individual....also...but still...not able to....

is any thing required me to do to the master table before forecasting it.....!! like (Data stationarity or etc)....any ideaz plz..

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