Electricity price forecasting is a critical tool in managing and planning energy markets worldwide. Accurate predictions underpin decision‐making for utilities, market traders, and policy makers by ...

Introduction: Moving Beyond Predictive Accuracy  Prediction has been traditionally the backbone of applied data science. From ...

Many government contractors still rely on fragmented systems and static spreadsheets to project what’s ahead. That approach may work for tracking awarded contracts, but it fails to support confident ...

Bayesian model averaging (BMA) is a popular ensemble-based postprocessing approach where the weighted average of the individual members is used to generate predictive forecasts. As the BMA formulation ...

This article compares the skill of medium-range probabilistic quantitative precipitation forecasts (PQPFs) generated via two postprocessing mechanisms: 1) the mixed-type meta-Gaussian distribution ...

Learn to apply Bayes' theorem in financial forecasting for insightful, updated predictions. Enhance decision-making with ...

The probability in weather forecasts leaves many people perplexed on if, or when, they should continue with plans, cancel or delay. As summer ramps up across North America, millions of travelers, ...

Future events are far from certain in the business world. This is especially true for smaller businesses, which tend to have more volatility than larger organizations, or newer businesses without a ...

Americans have long been familiar with “horse race” polls that accompany elections in the United States. But since 2008, a new polling tool has gained prominence, one that not only suggests which ...

If people with epilepsy could get “seizure warnings” akin to thunderstorm warnings, their neurological disorder might be less disruptive to their lives. That’s the goal driving work at the University ...