Fits the space-time Epidemic Type Aftershock Sequence
('ETAS') model to earthquake catalogs using a stochastic 'declustering'
approach. The 'ETAS' model is a 'spatio-temporal' marked point process
model and a special case of the 'Hawkes' process. The package is based
on a Fortran program by 'Jiancang Zhuang'
(available at < http://bemlar.ism.ac.jp/zhuang/software.html>),
which is modified and translated into C++ and C such that it
can be called from R. Parallel computing with 'OpenMP' is possible
on supported platforms.

This repository contains a copy of the R package 'ETAS'.

The Epidemic Type Aftershock Sequence (ETAS) model is a spatio-temporal marked point process model. The 'ETAS' package fits the ETAS model to an earthquake catalog.

Installation

To install the package, run the following in R:

require(devtools)

install_github('jalilian/ETAS')

If 'devtools' is not installed, you should first run:

install.packages('devtools')

Alternatively, the package can be installed by

require(githubinstall)

githubinstall('ETAS')

If 'githubinstall' is not installed, first run:

install.packages('githubinstall')

Parallel computing

As of version 0.3, a new C++ code is implemented using the Rcpp package which allows multi-thread parallel computing on multi-core processors with OpenMP and suported platforms. The argument nthreads in etas function determines the number of threads to be used in the parallel region of the code. The detectCores function in parallel package can be consulted to find out the overall number of available threads on a given machine:

parallel::detectCores()

Parallel computing (nthreads > 1) reduces the computation time for large earthquake catalogs. However, resource usage and limitations should be considered when setting nthreads.