ARIMA Model

ARIMA stands for AutoRegressive Integrated Moving Average, a statistical model used for analyzing and forecasting time-series data. It combines three elements: "AutoRegressive" indicates that past values influence current ones, "Integrated" means the data is made stationary by removing trends, and "Moving Average" accounts for past forecast errors. This model helps in understanding patterns in data like economic indicators, sales figures, or weather conditions, enabling informed predictions about future values based on historical information. Its flexibility and effectiveness make it popular in various fields, including finance and logistics.