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The ranking problem of earthquake forecasts is considered. We formulate simple statistical requirements to forecasting quality measure R and analyze some R-ranking methods on this basis, in particular, the pari-mutuel gambling method by…

Geophysics · Physics 2016-04-21 G. Molchan

Testing earthquake forecasts is essential to obtain scientific information on forecasting models and sufficient credibility for societal usage. We aim at enhancing the testing phase proposed by the Collaboratory for the Study of Earthquake…

Applications · Statistics 2026-02-03 Jonas R. Brehmer , Kristof Kraus , Tilmann Gneiting , Marcus Herrmann , Warner Marzocchi

Stochastic models of point patterns in space and time are widely used to issue forecasts or assess risk, and often they affect societally relevant decisions. We adapt the concept of consistent scoring functions and proper scoring rules,…

Probability forecasts of events are routinely used in climate predictions, in forecasting default probabilities on bank loans or in estimating the probability of a patient's positive response to treatment. Scoring rules have long been used…

Statistics Theory · Mathematics 2012-02-24 Tze Leung Lai , Shulamith T. Gross , David Bo Shen

Proper scoring rules are used to assess the out-of-sample accuracy of probabilistic forecasts, with different scoring rules rewarding distinct aspects of forecast performance. Herein, we re-investigate the practice of using proper scoring…

Probabilistic forecasts in the form of probability distributions over future events have become popular in several fields including meteorology, hydrology, economics, and demography. In typical applications, many alternative statistical…

Computation · Statistics 2018-07-31 Alexander Jordan , Fabian Krüger , Sebastian Lerch

Statistical tests of earthquake predictions require a null hypothesis to model occasional chance successes. To define and quantify `chance success' is knotty. Some null hypotheses ascribe chance to the Earth: Seismicity is modeled as…

Applications · Statistics 2022-09-21 Brad Luen , Philip B. Stark

There are several scoring rules that one can choose from in order to score probabilistic forecasting models or estimate model parameters. Whilst it is generally agreed that proper scoring rules are preferable, there is no clear criterion…

Statistics Theory · Mathematics 2012-07-25 Reason Lesego Machete

The use of tiered warnings and multicategorical forecasts are ubiquitous in meteorological operations. Here, a flexible family of scoring functions is presented for evaluating the performance of ordered multicategorical forecasts. Each…

Applications · Statistics 2022-05-02 Robert Taggart , Nicholas Loveday , Deryn Griffiths

We present an axiomatic approach to earthquake forecasting in terms of multi-component random fields on a lattice. This approach provides a method for constructing point estimates and confidence intervals for conditional probabilities of…

Geophysics · Physics 2013-10-29 V. Gertsik , M. Kelbert , A. Krichevets

Survival analysis deals with modeling the time until an event occurs, and accurate probability estimates are crucial for decision-making, particularly in the competing-risks setting where multiple events are possible. While recent work has…

Methodology · Statistics 2026-02-03 Julie Alberge , Tristan Haugomat , Gaël Varoquaux , Judith Abécassis

The evaluation of probabilistic forecasts plays a central role both in the interpretation and in the use of forecast systems and their development. Probabilistic scores (scoring rules) provide statistical measures to assess the quality of…

Methodology · Statistics 2020-12-24 Hailiang Du

When predicting future events, it is common to issue forecasts that are probabilistic, in the form of probability distributions over the range of possible outcomes. Such forecasts can be evaluated using proper scoring rules. Proper scoring…

Computation · Statistics 2023-05-15 Sam Allen

Recently a likelihood-based methodology has been developed by the Collaboratory for the Study of Earthquake Predictability (CSEP) with a view to testing and ranking seismicity models. We analyze this approach from the standpoint of possible…

Geophysics · Physics 2011-08-19 George Molchan

A multicomponent random process used as a model for the problem of space-time earthquake prediction; this allows us to develop consistent estimation for conditional probabilities of large earthquakes if the values of the predictor…

Geophysics · Physics 2009-04-28 V. M. Ghertzik

Predictive benchmarking, the evaluation of machine learning models based on predictive performance and competitive ranking, is a central epistemic practice in machine learning research and an increasingly prominent method for scientific…

Machine Learning · Computer Science 2025-10-28 Timo Freiesleben , Sebastian Zezulka

This paper presents a framework for decision-making regarding post-earthquake assessment of instrumented buildings in a manner consistent with performance-based design criteria. This framework is achieved by simultaneously combining and…

Signal Processing · Electrical Eng. & Systems 2020-02-27 Milad Roohi , Eric M. Hernandez

Earthquakes are commonly estimated using physical seismic stations, however, due to the installation requirements and costs of these stations, global coverage quickly becomes impractical. An efficient and lower-cost alternative is to…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Daniele Rege Cambrin , Isaac Corley , Paolo Garza , Peyman Najafirad

Scoring rules are used to evaluate the quality of predictions that take the form of probability distributions. A scoring rule is strictly proper if its expected value is uniquely minimized by the true probability distribution. One of the…

Methodology · Statistics 2021-04-05 Zoe Guan

No proven method is currently available for the reliable short time prediction of earthquakes (minutes to months). However, it is possible to make probabilistic hazard assessments for earthquake risk. These are primarily based on the…

Statistical Mechanics · Physics 2020-01-29 James R. Holliday , Kazuyoshi Z. Nanjo , Kristy F. Tiampo , John B. Rundle , Donald L. Turcotte
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