Jan-23-2019, 09:37 AM (This post was last modified: Jan-23-2019, 12:51 PM by Larz60+. Edited 1 time in total.)

hi

i am using the software PyCharm(2018.1) software to create ARIMA model in pyhthon

here is the model that i have created:

the error that i have got when i run the model:

any help will be appreciated

Thank you

Please post all code, output and errors (it it's entirety) between their respective tags. Refer to BBCode help topic on how to post. Use the "Preview Post" button to make sure the code is presented as you expect before hitting the "Post Reply/Thread" button.

I fixed for you this time. Please use code tags going forward. Thank You.

i am using the software PyCharm(2018.1) software to create ARIMA model in pyhthon

here is the model that i have created:

def arima_Model_Static_PlotErrorAC_PAC(series, arima_order): # prepare training dataset X = series # print(X) exit() train_size = int(len(X) * 0.50) # 0.50 train, test = X[0:train_size], X[train_size:] history = [x for x in train] # make predictions print(len(history)) print(history) exit() errorList=list() expected= list() predictions = list() obs = list() for t in range(len(test)): model = ARIMA(history, order=arima_order) #exit() model_fit = model.fit(disp=False, transparams=False) yhat = model_fit.forecast()[0] #model_fit.forecast()[0] exit() predictions.append(yhat) obs = test[t] history.append(obs) expected.append(obs) errorResidualExpePred = obs - yhat errorList.append(errorResidualExpePred) print('epoch=%i, predicted=%f, expected=%f' % (t, yhat, obs)) mse = mean_squared_error(test, predictions) rmse = sqrt(mse) print(model_fit.summary()) print(rmse) return errorListi called this model as follow:

series=np.array(diffARIMA) #series=colDataSet arima_order=(11,0,32) outputResidualError=arima_Model_Static_PlotErrorAC_PAC(series, arima_order)also the values of p, d, q are well chosen by applying the following rules

- remove the seasonality
- p: lag value where PACF cuts off first, so p=11.

- d=0 because apply the ADF test test and found my series is stationary so no differentiate has been done

- q: lag value where ACF chart crosses the upper confidence interval first, so q=32

- p: lag value where PACF cuts off first, so p=11.

the error that i have got when i run the model:

```
Error:
File "C:/109_personel/112_pyCharmArima/Presentation.py", line 296, in arima_Model_Static_PlotErrorAC_PAC
model_fit = model.fit(disp=False, transparams=False)
File "C:\109_personel\112_pyCharmArima\venv\lib\site-packages\statsmodels\tsa\arima_model.py", line 946, in fit
start_ar_lags)
File "C:\109_personel\112_pyCharmArima\venv\lib\site-packages\statsmodels\tsa\arima_model.py", line 562, in _fit_start_params
start_params = self._fit_start_params_hr(order, start_ar_lags)
File "C:\109_personel\112_pyCharmArima\venv\lib\site-packages\statsmodels\tsa\arima_model.py", line 541, in _fit_start_params_hr
raise ValueError("The computed initial AR coefficients are not "
ValueError: The computed initial AR coefficients are not stationary
You should induce stationarity, choose a different model order, or you can
pass your own start_params.
```

Finally i would like to mention that if a apply my model by selecting the following arima orderarima_order=(11,0,0) arima_order=(0,0,16)my modele is well executed

any help will be appreciated

Thank you

**Larz60+**wrote Jan-23-2019, 12:51 PM:Please post all code, output and errors (it it's entirety) between their respective tags. Refer to BBCode help topic on how to post. Use the "Preview Post" button to make sure the code is presented as you expect before hitting the "Post Reply/Thread" button.

I fixed for you this time. Please use code tags going forward. Thank You.