README.md

In tjmckinley/SimBIID: Simulation-Based Inference Methods for Infectious Disease Models

SimBIID

R package that implements various simulation-based inference routines for infectious disease models. At the current time it is mainly used for education purposes.

Package provides some code to run simulations of state-space models, and then use these in the ABC-SMC algorithm of Toni et al. (2009) and the bootstrap particle filter based particle MCMC algorithm (Andrieu et al., 2010). Also provides functions to plot and summarise the outputs.

A detailed vignette is provided at: https://tjmckinley.github.io/SimBIID_tutorial/

To install package

The package depends on the Rcpp and RcppArmadillo packages, which require the installation of the correct C++ compilers. The guidance below is taken from Sections 2.1.1, 2.1.2 or 2.1.3 here:

https://teuder.github.io/rcpp4everyone_en/020_install.html

Windows

Install Rtools.

(Make sure you tick the option to add Rtools to the PATH whilst installing.)

Mac

Install Xcode command line tools. Execute the command xcode-select --install in a Terminal.

You might also need to install the gfortran libraries from:

https://cran.r-project.org/bin/macosx/tools/gfortran-6.1.pkg

Linux

Install gcc and related packages (you might also need gcc-fortran for some of the dependencies).

In Ubuntu Linux, execute the command sudo apt-get install r-base-dev in a Terminal.

Install package

Once the compilers have been installed, then the CRAN version can be installed in the usual way, e.g.

install.packages("SimBIID")

Alternatively, the development version can be installed from source using the remotes package in R. That is, install the remotes package and then run:

library(remotes)
install_github("tjmckinley/SimBIID")

tjmckinley/SimBIID documentation built on Sept. 11, 2022, 11:58 a.m.