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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
```{r setup, include = FALSE}
dir.create(file.path(tempdir(), "sims"))
knitr::opts_knit$set(root.dir = file.path(tempdir(), "sims"))
```
# simcases
<!-- badges: start -->
[](https://www.tidyverse.org/lifecycle/#experimental)
[](https://www.travis-ci.com/audrey-b/simcases)
[](https://ci.appveyor.com/project/audrey-b/simcases/branch/master)
[](https://codecov.io/gh/audrey-b/simcases?branch=master)
[](https://www.gnu.org/licenses/gpl-3.0.html)
[](https://cran.r-project.org/package=simcases)
<!-- badges: end -->
simcases is an R package to simplify the conduct of simulation studies across multiple cases/scenarios.
## Installation
To install the latest release version from [CRAN](https://cran.r-project.org)
```r
install.packages("simcases")
```
To install the latest development version from [GitHub](https://github.com/audrey-b/simcases)
```r
# install.packages("remotes")
remotes::install_github("audrey-b/simcases")
```
## Demonstration
First, define the likelihood, constants, parameters and other characteristics of the models to use for the simulations.
```{r}
library(simcases)
lik = "for(i in 1:10){
a[i] ~ dnorm(mu, 1/sigma^2)}"
const = list(mu=0)
sigma1 = list(sigma=1)
sigma2 = list(sigma=2)
all = ".*"
a = "a"
```
Specify the models to use. The first row is a header and the following rows each describe a model.
```{r}
models_sims = "code constants parameters monitor
lik const sigma1 a
lik const sigma2 a
lik const sigma1 all
lik const sigma2 all"
```
Simulate data. The results are written to files.
```{r}
set.seed(10)
smc_simulate(models = models_sims,
nsims = 3,
exists = NA,
ask = FALSE)
```
Analyse data according to specific cases (scenarios).
```{r}
prior <- "sigma ~ dunif(0, 6)"
sigma <- "sigma"
models_analysis <- "code code.add monitor
lik prior sigma
lik prior sigma"
cases <- "sims analyse
1 1
2 1
3 2
4 2"
smc_analyse(models = models_analysis,
cases = cases,
mode = simanalyse::sma_set_mode("quick"))
```
Evaluate the performance of the models across the cases (scenarios)
```{r}
smc_evaluate(cases, monitor="sigma")
```
Have a look at the files created.
```{r}
files <- list.files(getwd(), recursive=TRUE, all.files=TRUE)
print(files)
```
Load one file.
```{r}
readRDS(file.path(getwd(), files[3]))
```
## Additional features
When a large number of models is used, it can be more convenient to specify models as data frames to facilitate query and manipulation. The example above may be reproduced as follows.
```{r}
models <- tibble::tribble(
~parameters, ~monitor,
"sigma1", "a",
"sigma2", "all"
)
models <- tidyr::expand(models, parameters, monitor)
models$code <- "lik"
models$constants <- "const"
models
set.seed(10)
smc_simulate(models = models,
nsims = 3,
fun = identity,
exists = NA,
ask = FALSE)
```
## Contribution
Please report any [issues](https://github.com/audrey-b/simcases/issues).
[Pull requests](https://github.com/audrey-b/simcases/pulls) are always welcome.
Please note that this project is released with a [Contributor Code of Conduct](https://github.com/audrey-b/simcases/blob/master/CODE_OF_CONDUCT.md).
By contributing, you agree to abide by its terms.