A review of predictive uncertainty estimation with machine learning

H Tyralis, G Papacharalampous - Artificial Intelligence Review, 2024 - Springer
Predictions and forecasts of machine learning models should take the form of probability
distributions, aiming to increase the quantity of information communicated to end users …

A review of probabilistic forecasting and prediction with machine learning

H Tyralis, G Papacharalampous - arXiv preprint arXiv:2209.08307, 2022 - arxiv.org
Predictions and forecasts of machine learning models should take the form of probability
distributions, aiming to increase the quantity of information communicated to end users …

Forecaster's dilemma: extreme events and forecast evaluation

S Lerch, TL Thorarinsdottir, F Ravazzolo, T Gneiting - Statistical Science, 2017 - JSTOR
In public discussions of the quality of forecasts, attention typically focuses on the predictive
performance in cases of extreme events. However, the restriction of conventional forecast …

An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile

C Candia, R Herrera - Journal of Empirical Finance, 2024 - Elsevier
This work provides a selective review of the most recent dynamic models based on extreme
value theory, in terms of their ability to forecast financial losses through different risk …

Hydrological post-processing for predicting extreme quantiles

H Tyralis, G Papacharalampous - Journal of Hydrology, 2023 - Elsevier
Hydrological post-processing using quantile regression algorithms constitutes a prime
means of estimating the uncertainty of hydrological predictions. Nonetheless, conventional …

Local scale invariance and robustness of proper scoring rules

D Bolin, J Wallin - Statistical Science, 2023 - projecteuclid.org
Averages of proper scoring rules are often used to rank probabilistic forecasts. In many
cases, the individual terms in these averages are based on observations and forecasts from …

[PDF][PDF] Scale dependence: Why the average CRPS often is inappropriate for ranking probabilistic forecasts

D Bolin, J Wallin - arXiv preprint arXiv:1912.05642, 2019 - researchgate.net
Averages of proper scoring rules are often used to rank probabilistic forecasts. In many
cases, the individual observations and their predictive distributions in these averages have …

Exceedance probability estimation for a quality test consisting of multiple measurements

S Tamminen, I Juutilainen, J Röning - Expert systems with applications, 2013 - Elsevier
The purpose of this study was to develop methods for exceedance probability estimation in
the case of highly scattered measurement sets. The situation may occur when product …

[PDF][PDF] Local scale invariance and

D Bolin, J Wallin - Statistical Science, 2022 - repository.kaust.edu.sa
Averages of proper scoring rules are often used to rank probabilistic forecasts. In many
cases, the individual terms in these averages are based on observations and forecasts from …

[PDF][PDF] Probabilistic forecasting and comparative model assessment, with focus on extreme events

S Lerch - 2016 - core.ac.uk
Probabilistic forecasts in the form of probability distributions over future quantities or events
allow to quantify the prediction uncertainty and are essential for informed decision making …