Package: bayesianETAS 1.0.3

bayesianETAS: Bayesian Estimation of the ETAS Model for Earthquake Occurrences

The Epidemic Type Aftershock Sequence (ETAS) model is one of the best-performing methods for modeling and forecasting earthquake occurrences. This package implements Bayesian estimation routines to draw samples from the full posterior distribution of the model parameters, given an earthquake catalog. The paper on which this package is based is Gordon J. Ross - Bayesian Estimation of the ETAS Model for Earthquake Occurrences (2016), available from the below URL.

Authors:Gordon J. Ross

bayesianETAS_1.0.3.tar.gz
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bayesianETAS.pdf |bayesianETAS.html
bayesianETAS/json (API)

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

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

4 exports 1 stars 0.09 score 0 dependencies 10 scripts 193 downloads

Last updated 8 years agofrom:c62be50ef0. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 28 2024
R-4.5-win-x86_64NOTEAug 28 2024
R-4.5-linux-x86_64NOTEAug 28 2024
R-4.4-win-x86_64NOTEAug 28 2024
R-4.4-mac-x86_64NOTEAug 28 2024
R-4.4-mac-aarch64NOTEAug 28 2024
R-4.3-win-x86_64NOTEAug 28 2024
R-4.3-mac-x86_64NOTEAug 28 2024
R-4.3-mac-aarch64NOTEAug 28 2024

Exports:maxLikelihoodETASsampleETASposteriorsimulateETASsimulateNHPP

Dependencies: