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https://github.com/sempwn/bennu

Bayesian Estimation of Naloxone Numbers Underreporting
https://github.com/sempwn/bennu

bayesian-data-analysis naloxone r r-package rstats stan

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Bayesian Estimation of Naloxone Numbers Underreporting

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README

        

---
output: github_document
---

```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```

# bennu

**B**ayesian **E**stimation of **N**aloxone **N**umbers **U**nderreporting (**BENNU**)

*The package name comes from the Welsh word for "to finish" (pronounced benn-y)*


[![R-CMD-check](https://github.com/sempwn/bennu/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/sempwn/bennu/actions/workflows/R-CMD-check.yaml)
[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[![Codecov test coverage](https://codecov.io/gh/sempwn/bennu/branch/main/graph/badge.svg)](https://app.codecov.io/gh/sempwn/bennu?branch=main)
![GitHub](https://img.shields.io/github/license/sempwn/bennu?style=plastic)

An R package 📦 for generating estimates of total naloxone kit numbers distributed and used from naloxone kit orders data.

## Installation

You can install the released version of bennu from [CRAN](https://CRAN.R-project.org) with:

``` r
install.packages("bennu")
```

And the development version from [GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("sempwn/bennu")
```
## Example

This example runs output for test data generated by the package:

```{r example, warning=FALSE}
library(bennu)
library(rstan)
library(bayesplot)

rstan_options(auto_write = TRUE)
options(mc.cores = parallel::detectCores(logical = FALSE))

## basic example code
d <- generate_model_data()
# note iter should be at least 2000 to generate a reasonable posterior sample
fit <- est_naloxone(d,iter=500)
mcmc_pairs(fit, pars = c("sigma","mu0","zeta"),
off_diag_args = list(size = 1, alpha = 0.5))
```

An overall summary of the model output can also be provided as a data frame

```{r, warning=FALSE}
kit_summary_table(fit, data = d)
```

## Getting help

If you encounter a clear bug, please file an issue with a minimal reproducible example on [GitHub](https://github.com/sempwn/bennu/issues).