Package: ETASbootstrap 0.2.0

ETASbootstrap: Bootstrap Confidence Interval Estimation for 'ETAS' Model Parameters

The 2-D spatial and temporal Epidemic Type Aftershock Sequence ('ETAS') Model is widely used to 'decluster' earthquake data catalogs. Usually, the calculation of standard errors of the 'ETAS' model parameter estimates is based on the Hessian matrix derived from the log-likelihood function of the fitted model. However, when an 'ETAS' model is fitted to a local data set over a time period that is limited or short, the standard errors based on the Hessian matrix may be inaccurate. It follows that the asymptotic confidence intervals for parameters may not always be reliable. As an alternative, this package allows for the construction of bootstrap confidence intervals based on empirical quantiles for the parameters of the 2-D spatial and temporal 'ETAS' model. This version improves on Version 0.1.0 of the package by enabling the study space window (renamed 'study region') to be polygonal rather than merely rectangular. A Japan earthquake data catalog is used in a second example to illustrate this new feature.

Authors:Renjie Peng [aut, cre], Pierre Dutilleul [aut], Christian Genest [aut]

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ETASbootstrap/json (API)

# Install 'ETASbootstrap' in R:
install.packages('ETASbootstrap', repos = c('https://rjpeng98.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/rjpeng98/etasbootstrap/issues

Datasets:

On CRAN:

3 exports 0.83 score 23 dependencies 2 scripts 158 downloads

Last updated 2 months agofrom:0462c073c1. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 01 2024
R-4.5-winNOTESep 01 2024
R-4.5-linuxNOTESep 01 2024
R-4.4-winNOTESep 01 2024
R-4.4-macNOTESep 01 2024
R-4.3-winOKSep 01 2024
R-4.3-macOKSep 01 2024

Exports:ETAS_Bootssimulate_aftershockssimulate_background_earthquakes

Dependencies:abinddeldirdotCall64ETASfieldsgoftestlatticemapsMASSMatrixnlmepolyclipRcppspamspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilstensorviridisLite