What does "Residual Component" mean?

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The residual component refers to the part of a system or data that captures the changes or fluctuations not explained by the main model. In simpler terms, it represents the differences that are left over after accounting for the main behavior or trend of the data.

In many real-world situations, data can change over time due to various factors, making it difficult to predict accurately. The residual component helps in identifying these changes, allowing for better adjustments and predictions.

By focusing on this leftover part of the data, models can be improved to handle unexpected variations. This approach leads to more accurate forecasts and helps in effectively incorporating new information as it becomes available.