Inference for earthquake models: A self-correcting model

DOI10.1016/0304-4149(84)90009-7zbMath0543.62068OpenAlexW2090248608WikidataQ56763934 ScholiaQ56763934MaRDI QIDQ796230

D. Vere-Jones, Yosihiko Ogata

Publication date: 1984

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4149(84)90009-7

zbMATH Keywords

weak convergencelikelihood ratio statisticmaximum likelihood estimatesPoisson processgoodness of fit testconsistentconditional intensity functionnonstandard casepoint process modelsrandom Fisher information matrixself-correcting point process

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Non-Markovian processes: estimation (62M09) Seismology (including tsunami modeling), earthquakes (86A15) Applications of statistics (62P99) Inference from stochastic processes (62M99) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (14)

Asymptotic inference for semimartingale models with singular parameter points ⋮ On a singularity occurring in a self-correcting point process model ⋮ Estimating a parametric trend component in a continuous-time jump-type process ⋮ Exact simulation of extrinsic stress-release processes ⋮ Histogram maximum likelihood estimator in the multiplicative intensity model ⋮ A note on kernel smoothing of an estimator of a periodic function in the multiplicative intensity model ⋮ Some problems in nonparametric inference for the stress release process related to the local time ⋮ Parameter estimation for the simple self-correcting point process ⋮ Local asymptotic mixed normality for semimartingale experiments ⋮ Consistent parametric estimation of the intensity of a spatial-temporal point process ⋮ TCP and iso-stationary transformations ⋮ ``Explosive processes in recidivism and other reinforcement models of learning ⋮ Hypotheses testing: Poisson versus stress-release ⋮ Ergodic theorems for stress release processes

Cites Work

• Asymptotic optimal inference for non-ergodic models
• Asymptotic tests of composite hypotheses for non-ergodic type stochastic processes
• The asymptotic behaviour of maximum likelihood estimators for stationary point processes
• A self-correcting point process
• Maximum-Likelihood Estimation of Parameters Subject to Restraints
• On the moments of a self-correcting process
• Regular point processes and their detection
• Asymptotic Theory of Certain "Goodness of Fit" Criteria Based on Stochastic Processes
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