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I have tried to generate/write equation for forecasting using ARIMA models. But I think my equations were wrong and I am stuck with it. Kindly please help me to obtain equations for

1.(ARIMA (0,1,2) ma1 ma2= -0.1704, 0.4193 s.e s.e= 0.1259, 0.1646 σ^2, log likelihood= 127.7, -179.84

  1. SARIMA (1,0,0)(0,1,0)12 ar1 = 0.7076 s.e = 0.1304 σ^2, log likelihood= 450.1, -160.89

  2. ARIMA (0,1,3)

ma1, ma2, ma3= -0.4932, 0.1227, -0.3997 s.e s.e s.e= 0.1326, 0.179, 0.1384 σ^2 log likelihood= 333.2, -202.12

  1. SARIMA (1,0,0)(1,1,0)12

ar1, sar1= 0.4605, -0.722 s.e s.e= 0.1463, 0.1061 σ^2 log likelihood= 423.4, -163.46

  1. ARIMA (0,1,1) ma1= -0.464 s.e= 0.167 σ^2 log likelihood= 2384, -249.05

  2. ARIMA (1,1,1) ar1, ma1= 0.394, -0.9023 s.e s.e= 0.1804, 0.0898 σ^2 log likelihood= 393.5, -206.57

  3. ARIMA (0,1,1) ma1= -0.7823 s.e = 0.0987 σ^2 log likelihood= 499.4, -212.67

Is there anything I am missing for formulating the equation?

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marked as duplicate by whuber Apr 7 '17 at 16:44

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

  • $\begingroup$ This question cannot be answered without the time series data. You may not need to look at so many models when you look at partial autocorrelation and autocorrelation functions. $\endgroup$ – Michael Chernick Apr 7 '17 at 16:25
  • $\begingroup$ Please see stats.stackexchange.com/search?q=arima+equation for many similar questions. $\endgroup$ – whuber Apr 7 '17 at 16:44