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In time series forecasting, it is important to consider the full probability distribution of the predictions rather than a single point estimate. This provides a more accurate representation of the uncertainty around the forecasts and allows better decision-making. TimeGPT supports uncertainty quantification through quantile forecasts and prediction intervals.

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Why Consider the Full Probability Distribution?

When you focus on a single point prediction, you lose valuable information about the range of possible outcomes. By quantifying uncertainty, you can:
  • Identify best-case and worst-case scenarios
  • Improve risk management and contingency planning
  • Gain confidence in decisions that rely on forecast accuracy

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What You Will Learn

Quantile Forecasts

Learn how to compute quantile forecasts using TimeGPT.

Prediction Intervals

Discover how to create prediction intervals with TimeGPT.
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