# Assessment of Point Process Models for Earthquake Forecasting

arXiv: https://arxiv.org/abs/1312.5934 · HTML: https://mlsanity.com/paper/1312.5934/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Dec 2013.

## Built on by (most cited first, 2 of 2)

- [Neural Temporal Point Processes: A Review](https://mlsanity.com/paper/2104.03528/) (2021)
- [TPP-Gaze: Modelling Gaze Dynamics in Space and Time with Neural Temporal Point Processes](https://mlsanity.com/paper/2410.23409/) (2024)

## Abstract (arXiv)

Models for forecasting earthquakes are currently tested prospectively in well-organized testing centers, using data collected after the models and their parameters are completely specified. The extent to which these models agree with the data is typically assessed using a variety of numerical tests, which unfortunately have low power and may be misleading for model comparison purposes. Promising alternatives exist, especially residual methods such as super-thinning and Voronoi residuals. This article reviews some of these tests and residual methods for determining the goodness of fit of earthquake forecasting models.