Voronoi residual analysis of spatial point process models with applications to California earthquake forecasts

DOI10.1214/14-AOAS767zbMath1454.62281arXiv1501.06387OpenAlexW3098677353MaRDI QIDQ2258576

Frederic Paik Schoenberg, Andrew Bray, Ka Wong, Christopher David Barr

Publication date: 26 February 2015

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1501.06387

zbMATH Keywords

seismologyVoronoi tessellationspoint patternsepidemic-type aftershock sequence modelshector mineresiduals analysis

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Applications of statistics to environmental and related topics (62P12) Seismology (including tsunami modeling), earthquakes (86A15) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (6)

A review of self-exciting spatio-temporal point processes and their applications ⋮ Model Checking for Hidden Markov Models ⋮ Estimating Covid-19 transmission time using Hawkes point processes ⋮ Comparative evaluation of point process forecasts ⋮ Including covariates in a space-time point process with application to seismicity ⋮ Space-time inhomogeneous background intensity estimators for semi-parametric space-time self-exciting point process models

Uses Software

• pyuvdata

Cites Work

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