1- Check again the stationarity of the time series using augmented Dickey-Fuller (ADF) test . 2- Try to increase the number of predictors ( independent variables). 3- Try to increase the sample size (in case of monthly data, to use at least 4 years data.
Read moreHow do you predict in Python?
Python predict() function enables us to predict the labels of the data values on the basis of the trained model. The predict() function accepts only a single argument which is usually the data to be tested.
Read moreIs ARIMA a predictive model?
ARIMA, short for ‘AutoRegressive Integrated Moving Average’, is a forecasting algorithm based on the idea that the information in the past values of the time series can alone be used to predict the future values.
Read moreWhy is the ARIMA model good?
It is widely used in demand forecasting, such as in determining future demand in food manufacturing. That is because the model provides managers with reliable guidelines in making decisions related to supply chains . ARIMA models can also be used to predict the future price of your stocks based on the past prices.
Read moreAre ARIMA models good?
ARIMA models are not generally preferred over any other time series analysis method . There are certainly not preferred when the series demonstrate non-stationaries unable to be modelled using the ARIMA framework.
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