# bang

### Bayesian Analysis, No Gibbs

### What does bang do?

Provides functions for the Bayesian analysis of some simple
commonly-used models, without using Markov Chain Monte Carlo (MCMC)
methods such as Gibbs sampling. The ‘rust’ package https://cran.r-project.org/package=rust is used to
simulate a random sample from the required posterior distribution, using
the ratio-of-uniforms method. Currently three conjugate hierarchical
models are available: beta-binomial, gamma-Poisson and a 1-way Analysis
of Variance (ANOVA). Advantages of the ratio-of-uniforms method over
MCMC in this context are that the user is not required to set tuning
parameters nor to monitor convergence and a random posterior sample is
produced.

### A simple example

The `hef`

function samples from the posterior distribution
of the parameters of certain hierarchical exponential family models. The
following code performs essentially the same analysis of the rat tumor
data using a beta-binomial hierarchical model that appears in Section
5.3 of Gelman, A., Carlin, J. B., Stern, H. S. Dunson, D. B., Vehtari,
A. and Rubin, D. B. (2014) Bayesian Data Analysis. Chapman & Hall /
CRC. http://www.stat.columbia.edu/~gelman/book.

```
library(bang)
rat_res <- hef(model = "beta_binom", data = rat)
plot(rat_res)
```

### Installation

To get the current released version from CRAN: