Auto-calibration of forecast sequences equals measure-valued martingales, enabling a statistical test for calibration of updating predictions.
The Review of Economics and Statistics 69, 667–674
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Neural network-parameterized regression splines enable joint optimization of forecast quality and stability in distribution-free probabilistic time series models by penalizing dissimilarities from forecast updates.
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Calibrated Probability Forecast Sequences and Measure-Valued Martingales
Auto-calibration of forecast sequences equals measure-valued martingales, enabling a statistical test for calibration of updating predictions.
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Stabilizing distribution-free probabilistic forecasts
Neural network-parameterized regression splines enable joint optimization of forecast quality and stability in distribution-free probabilistic time series models by penalizing dissimilarities from forecast updates.