README.Rmd

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# ETAS.inlabru

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R package that implements the ETAS Hawkes process for modelling seismicity

Online documentation: https://edinburgh-seismicity-hub.github.io/ETAS.inlabru/

## Authors

- [Dr Francesco Serafini](https://scholar.google.com/citations?user=NVDOxTcAAAAJ&hl=en)
- [Dr Mark Naylor](https://blogs.ed.ac.uk/mnaylor/) , School of GeoSciences, University of Edinburgh
- [Prof Finn Lindgren](https://www.maths.ed.ac.uk/~flindgre/) , School of Mathematics, University of Edinburgh
- [Dr Kirsty Bayliss](https://www.linkedin.com/in/kirsty-bayliss-9a6604a1/?originalSubdomain=uk) , Global Earthquake Model (GEM)

## Funding

- This study was funded by yhe Real-Time Earthquake Risk Reduction for a Resilient Europe
  [RISE project](http://www.rise-eu.org/home/) , which has received funding from the European
  Union's Horizon 2020 Research and Innovation Program under grant Agreement 821115. 
- Naylor was additionally funded by the NSFGEO-NERC grant NE/R000794/1. 
- Bayliss was funded by an EPSRC Studentship.

## Installation

For ETAS.inlabru to work, we need to install both R-INLA and inlabru:

For inlabru (see https://inlabru-org.github.io/inlabru/):

* CRAN release,
``` r
install.packages("inlabru")
```
* or development version,
``` r
# install.packages("remotes")
remotes::install_github("inlabru-org/inlabru")
```

For R-INLA (see https://www.r-inla.org/download-install):
``` r
install.packages(
  "INLA",
  repos = c(getOption("repos"), INLA="https://inla.r-inla-download.org/R/testing"),
  dep = TRUE
)
```

You can install the development version of ETAS.inlabru from [GitHub](https://github.com/) with
``` r
# install.packages("remotes")
remotes::install_github("edinburgh-seismicity-hub/ETAS.inlabru")
```

## Terminology and planning suggestions

### File structure in package

- ETAS.triggering.function.R : Contains the ETAS specific model functions
- HawkesProcess.R : Generic Hawkes code that is intended for integration back into inlabru
- generateSyntheticCatalogues.R : Contains the iterative Hawkes functions for generating triggered events but the actual triggering functions reside in the ETAS file above so we could introduce other models here
- temporalBinning.R : Code to generate time bins to make integration scheme efficient
- plottingFunctions.R : lets put all the standard plotting functions into here
- setupInlabruInputs.R : Put the functions for generating input.list in here

## Terminology

- Let's be specific about when we are doing just temporal so we have clear function names for the spatial and spatial-temporal later on
- I changed the theta from `c(mu, K, ...)` to a `df <- data.frame(mu=mu, K=K, alpha=alpha, c=c, p=p)`. This means we should refer to the values as `df$mu` which is unambiguous etc

# What has been done

## Implemented

- Generation of synthetic ETAS catalogues by `ETAS.inlabru` with a demonstration in the notebook

## In development

- Add inversion modelling based on original code
- Modify the implementation so that the generic Hawkes code can go into
  inlabru and the ETAS triggering function code stay in this package

## Roadmap

- Integrate spatial modelling