Residual analysis methods for space-time point processes with applications to earthquake forecast models in California

DOI10.1214/11-AOAS487zbMath1454.62282arXiv1202.6487OpenAlexW2083406753MaRDI QIDQ765997

Robert Alan Clements, Frederic Paik Schoenberg, Danijel Schorlemmer

Publication date: 22 March 2012

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

Full work available at URL: https://arxiv.org/abs/1202.6487

zbMATH Keywords

superpositionPearson residualsdeviance residualsrescaled residualssuper-thinned residualsthinned residuals

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Seismology (including tsunami modeling), earthquakes (86A15) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (4)

Estimating Covid-19 transmission time using Hawkes point processes ⋮ Comparative evaluation of point process forecasts ⋮ Voronoi residual analysis of spatial point process models with applications to California earthquake forecasts ⋮ Assessment of point process models for earthquake forecasting

Uses Software

• spatial
• pyuvdata

Cites Work

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• Non‐ and semi‐parametric estimation of interaction in inhomogeneous point patterns
• An Introduction to the Theory of Point Processes
• Assessing Spatial Point Process Models Using Weighted K-functions: Analysis of California Earthquakes
• Residual Analysis for Spatial Point Processes (with Discussion)
• Integrability of Expected Increments of Point Processes and a Related Random Change of Scale
• A new look at the statistical model identification

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