# How actually my time series models tells me about data behaviour? [closed]

I have different models namely AR, ARMA, ARIMA for different time series (in data set of 4449) stationary-3096, Non stationary-1353 , why this classification appears to be?

If I have $AR(p=1-5)$ and $AR(p >5)$ what does my data tell ?,

I have many time series which follows ARMA-1239 best models, some are AR-90 best model & ARIMA-7 best models out of 3096 stationary data set

Please, kindly tell me in philosophical/non-statistical way (because I didn't understand by term like normal/marginal distribution).

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 This is all rather unclear to me - are you saying you have 4,449 different time series? It seems like you're saying 90 of them only required AR terms, 1239 required MA terms as well, etc.. but I'm not sure. You'll have a much better chance at getting a good answer if you edit and give a clearer description of the data and the problem. – Macro Apr 30 '12 at 15:28 it seems to be confusing to you sir,don't worrytell me separate thing,without considering data size, 1) If I have AR(p=1−5) and AR(p>5) what does my data tell ?, 2) most of time series follows ARMA process than AR,(for each time series i calculate both models,best model selected on basis of lowest AIC value) – Sagar Nikam May 1 '12 at 12:47 It might also help if you give some context, and describe exactly what problem you're trying to solve – naught101 May 2 '12 at 0:51

## closed as not a real question by Macro, gung, whuber♦Aug 14 '12 at 12:56

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