Autoregressive Models

Autoregressive models are statistical tools used to predict future values based on past data. Imagine you’re trying to guess tomorrow's temperature by looking at the temperatures from the past few days. An autoregressive model analyzes these past values to identify patterns and trends. It assumes that what happened before can inform what happens next. These models are widely used in fields like finance, weather forecasting, and economics to make informed predictions by leveraging historical information. Essentially, they help us understand how the past influences the future in various data-driven scenarios.