Re: [R] which model suits for these kind of data

From: Uwe Ligges <ligges_at_statistik.tu-dortmund.de>
Date: Thu, 24 Jun 2010 13:49:51 +0200

You are probably under Windows. The Menu to install from local zip files implies you specify a precompiled binary package.

Uwe Ligges

On 24.06.2010 06:12, vijaysheegi wrote:
>
> Hi ,
> i am trying to install tseries packages from local drive.i am getting
> .Please advise
>
> I am getting this errror
> Please advise
>
>> utils:::menuInstallLocal()
> Error in gzfile(file, "r") : cannot open the connection
> In addition: Warning message:
> In gzfile(file, "r") :
> cannot open compressed file 'timeSeries/DESCRIPTION', probable reason 'No
> such file or directory'
>>
>
>
> On 6/22/10, Gabor Grothendieck [via R]<
> ml-node+2263915-1199101214-288333_at_n4.nabble.com<ml-node%2B2263915-1199101214-288333_at_n4.nabble.com>>
> wrote:
>>
>> Try this:
>>
>> library(forecast)
>> f<- forecast(DF[,3]); f
>> plot(f)
>>
>>
>> On Tue, Jun 22, 2010 at 4:14 AM, vijaysheegi<[hidden email]<http://user/SendEmail.jtp?type=node&node=2263915&i=0>>
>> wrote:
>>
>>>
>>> Hi ,
>>> please help me which model is helpful for forecasting giving following
>>> inputs (inputs are not linear)
>>>
>>> sales date shopnuber total 20%profit 10%profit
>>> 2009-10-03 1 41891 2863 39028
>>> 2009-10-04 1 49152 7588 41564
>>> 2009-10-05 1 45804 23543 22261
>>> 2009-10-06 1 48395 48371 24
>>> 2009-10-07 1 48906 20204 28702
>>> 2009-10-08 1 47003 19442 27561
>>> 2009-10-09 1 46296 21635 24661
>>> 2009-10-10 1 45980 34791 11189
>>> 2009-10-11 1 48423 1483 46940
>>> 2009-10-12 1 48800 18500 30300
>>> 2009-10-13 1 40694 22068 18626
>>> 2009-10-14 1 47356 42361 4995
>>> 2009-10-15 1 41501 15964 25537
>>> 2009-10-16 1 44762 42296 2466
>>> 2009-10-17 1 48607 12023 36584
>>> 2009-10-18 1 47513 28275 19238
>>> 2009-10-19 1 44527 7927 36600
>>> 2009-10-20 1 43948 17981 25967
>>> 2009-10-21 1 43139 17682 25457
>>> 2009-10-22 1 42426 24454 17972
>>> 2009-10-23 1 43620 1689 41931
>>> 2009-10-24 1 40850 28595 12255
>>> 2009-10-25 1 41665 10339 31326
>>> 2009-10-26 1 46151 41662 4489
>>> 2009-10-27 1 41355 30207 11148
>>>
>>>
>>>
>>> With this data how to predict total sales for further 6 days.Someone
>> please
>>> help .(if we get totals sales we can obntain 20% and 10% profit)
>>>
>>> --
>>> View this message in context:
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>>> Sent from the R help mailing list archive at Nabble.com.
>>>
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>>
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>
>



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