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README.Rmd
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README.Rmd
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---
output: github_document
---
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/license/mit/)
[![R-CMD-check](https://github.com/sbfnk/fitR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/sbfnk/fitR/actions/workflows/R-CMD-check.yaml)
[![Codecov test coverage](https://codecov.io/gh/sbfnk/fitR/branch/main/graph/badge.svg)](https://app.codecov.io/gh/sbfnk/fitR?branch=main)
fitR: Functions for model fitting and inference
====
The functions contained in this package have been developed in support of a course on [Model fitting and inference for infectious disease dynamics](http://sbfnk.github.io/mfiidd/) run annually at the [London School of Hygiene & Tropical Medicine](https://www.lshtm.ac.uk).
The main purpose of this package is to be a teaching tool, and the implementation of inference algorithms in this package is not particularly efficient of stable. For vastly superior alternative options for fitting models to data in R we recommend to consider, amongst others
- [rstan](https://github.com/stan-dev/rstan), an interface to [Stan](https://mc-stan.org/).
- [pomp](https://github.com/kingaa/pomp), for partially observed Markov processes.
- [rbi](https://github.com/sbfnk/RBi), an interface to [LibBi](https://libbi.org/).
## Installation
The easiest way to install `fitR` is to use the `remotes` package:
```{r eval = FALSE}
# install.packages("remotes")
library(remotes)
install_github("sbfnk/fitR", dependencies = TRUE)
```
## Included data sets
The package includes a number of data sets that are used for the course. They havae been generated using the scripts in the `scripts/generate-data` directory of the corresponding [github repo](https://github.com/sbfnk/mfiidd).