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Prediction Intervals

A prediction interval is an estimate of an interval in which a future observation will fall, with a certain probability, given what has already been observed. Prediction intervals are often used in regression analysis.

Papers

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Showing 111–120 of 309 papers

TitleStatusHype
Conformal Prediction for Electricity Price Forecasting in the Day-Ahead and Real-Time Balancing Market—0
Density-Calibrated Conformal Quantile Regression—0
Confidence intervals for class prevalences under prior probability shift—0
Development and Evaluation of Conformal Prediction Methods for QSAR—0
Efficiency of conformalized ridge regression—0
Discriminative Learning of Prediction Intervals—0
Disease Momentum: Estimating the Reproduction Number in the Presence of Superspreading—0
Confidence-Nets: A Step Towards better Prediction Intervals for regression Neural Networks on small datasets—0
Bin-Conditional Conformal Prediction of Fatalities from Armed Conflict—0
An Empirical Analysis of Constrained Support Vector Quantile Regression for Nonparametric Probabilistic Forecasting of Wind Power—0
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