R help - Mar 2012 - how to find best model of time series?

i have data in one file below like  & (i have such type of file =200,each
file have below type of data)
>t
-0.15264004
0.056076439
-0.07276116
-0.00917326
-0.02069089
-0.00416232
-0.07225855
-0.02654577
-0.06131410
-0.09380202
0.057414014
-0.05239976
0.014397612
0.016145161
-0.00670587
0.018696335
0.036943654
-0.02450233
0.031161705
0.006513503
-0.02892329
-0.00831519
-0.00877744
-0.00634399
-0.02612019
-0.02531800
-0.01435533
0.011148840
-0.01893775
0.029859128
0.029878797
-0.00125987
0.031404385
0.035127606
-0.00191775
0.059797202
-0.03268047
-0.06026960
-0.02216465
-0.08145612
-0.02772806
-0.03171683
-0.02842562
-0.11807898
-0.01457311
-0.12612482
0.409631265
-0.06375234
>plot.ts(t)
i am new to time series,i get plot,but don't know which pattern this is?
tell me how to determine type of time series(seasonal,trend,irregular,etc)
& from 200 such file/plot ,which model should i select as best model for
forecasting future events




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Take a look at

example(HoltWinters)

Michael

On Tue, Mar 13, 2012 at 11:06 AM, sagarnikam123 <sagarnikam123 at
gmail.com> wrote:
> i have data in one file below like ?& (i have such type of file
=200,each
> file have below type of data)
>>t
> -0.15264004
> 0.056076439
> -0.07276116
> -0.00917326
> -0.02069089
> -0.00416232
> -0.07225855
> -0.02654577
> -0.06131410
> -0.09380202
> 0.057414014
> -0.05239976
> 0.014397612
> 0.016145161
> -0.00670587
> 0.018696335
> 0.036943654
> -0.02450233
> 0.031161705
> 0.006513503
> -0.02892329
> -0.00831519
> -0.00877744
> -0.00634399
> -0.02612019
> -0.02531800
> -0.01435533
> 0.011148840
> -0.01893775
> 0.029859128
> 0.029878797
> -0.00125987
> 0.031404385
> 0.035127606
> -0.00191775
> 0.059797202
> -0.03268047
> -0.06026960
> -0.02216465
> -0.08145612
> -0.02772806
> -0.03171683
> -0.02842562
> -0.11807898
> -0.01457311
> -0.12612482
> 0.409631265
> -0.06375234
>
>>plot.ts(t)
>
> i am new to time series,i get plot,but don't know which pattern this
is?
> tell me how to determine type of time series(seasonal,trend,irregular,etc)
> & from 200 such file/plot ,which model should i select as best model
for
> forecasting future events
>
>
>
>
> --
> View this message in context:
http://r.789695.n4.nabble.com/how-to-find-best-model-of-time-series-tp4469296p4469296.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

yes but giving error
> t<-read.table(file.choose())
> t<-ts(t)
> plot(t)
Hit <Return> to see next plot: 
> ht<-HoltWinters(t)
Error in decompose(ts(x[1L:wind], start = start(x), frequency = f),
seasonal) : 
  time series has no or less than 2 periods

what should i do? 

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On 14-03-2012, at 07:22, sagarnikam123 wrote:
> yes but giving error
>> t<-read.table(file.choose())
>> t<-ts(t)
>> plot(t)
> Hit <Return> to see next plot: 
>> ht<-HoltWinters(t)
> Error in decompose(ts(x[1L:wind], start = start(x), frequency = f),
> seasonal) : 
>  time series has no or less than 2 periods
> 
> what should i do? 
Read HoltWinters help thoroughly.
Your timeseries should have a frequency > 1.

So how about t <- ts(t, start=??, frequency=4)

Berend

yes,but i want AIC value to calculate for below value, using frequency =1 in
ts() function
>t 
-0.15264004 
0.056076439 
-0.07276116 
-0.00917326 
-0.02069089 
-0.00416232 
-0.07225855 
-0.02654577 
-0.06131410 
-0.09380202 
0.057414014 
-0.05239976 
0.014397612 
0.016145161 
-0.00670587 
0.018696335 
0.036943654 
-0.02450233 
0.031161705 
0.006513503 
-0.02892329 
-0.00831519 
-0.00877744 
-0.00634399 
-0.02612019 
-0.02531800 
-0.01435533 
0.011148840 
-0.01893775 
0.029859128 
0.029878797 
-0.00125987 
0.031404385 
0.035127606 
-0.00191775 
0.059797202 
-0.03268047 
-0.06026960 
-0.02216465 
-0.08145612 
-0.02772806 
-0.03171683 
-0.02842562 
-0.11807898 
-0.01457311 
-0.12612482 
0.409631265 
-0.06375234 


in short, i want to know which is best model if i have this type of
vectors(t) 200,each having 400 observations at respective time i.e.
1,2,3,4.....400


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