Arima time series model

1. What is ARIMA time series?
2. What is ARIMA model used for?
3. Is ARIMA time series forecasting?
4. Is ARIMA better than LSTM?

What is ARIMA time series?

An autoregressive integrated moving average, or ARIMA, is a statistical analysis model that uses time series data to either better understand the data set or to predict future trends. A statistical model is autoregressive if it predicts future values based on past values.

What is ARIMA model used for?

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.

Is ARIMA time series forecasting?

ARIMA models provide another approach to time series forecasting. Exponential smoothing and ARIMA models are the two most widely used approaches to time series forecasting, and provide complementary approaches to the problem.

Is ARIMA better than LSTM?

The comparison of the models was made by comparing the values of the MAPE error. When predicting 30 days, ARIMA is about 3.4 times better than LSTM.