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ACF of my dataset[![][1] Click for ACF image 2

These are my ACF and PACF of my data set . Can any one help me determine whether the data is stationary ? if so What order of AR , MA ?

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The periodicity in your (P)ACF plots strongly suggests seasonality of length slightly less than 0.02 of the cycle you defined. Since $7/365\approx 0.019$, I suspect that you have daily data, which you specified as frequency=365. We can't say much more.

Note that it is not very good practice to examine (P)ACF plots any more (the approach). Nowadays, it's better to choose models based on AIC, after determining any necessary differencing using appropriate methods. I suggest you look at ?forecast::auto.arima and FPP2.

If you do have daily data with possible intra-yearly seasonality, you may want to look at our tag.

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  • $\begingroup$ Yes its a daily data I used the auto.arima function and it resulted in following Series: myts ARIMA(1,0,0) with non-zero mean Coefficients: ar1 mean 0.2103 236.0485 s.e. 0.0284 65.4923 sigma^2 estimated as 3181549: log likelihood=-10569.71 AIC=21145.41 AICc=21145.43 BIC=21160.65 $\endgroup$ – kartik Jul 25 '18 at 17:13
  • $\begingroup$ Try clarifying that the more relevant seasonal cycle is of length 7, rather than 365: ts(..., frequency=7). I suspect that auto.arima() will then give you a seasonal model based on this frequency. $\endgroup$ – S. Kolassa - Reinstate Monica Jul 25 '18 at 19:51

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