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Curvilinear forecasting allows for a more flexible modeling approach that can capture nonlinear relationships between variables, which may be present in real-world data. This can result in more accurate predictions compared to linear forecasting methods.

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Q: What is the principal advantage of curvilinear forecasting?
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