# README.md In brr: Bayesian Inference on the Ratio of Two Poisson Rates

## brr package for R

Bayesian inference on the ratio of two Poisson rates.

### What does it do ?

Suppose you have two counts of events and, assuming each count follows a Poisson distribution with an unknown incidence rate, you are interested in the ratio of the two rates (or relative risk). The `brr` package allows to perform the Bayesian analysis of the relative risk using the natural semi-conjugate family of prior distributions, with a default non-informative prior (see references).

### Install

You can install:

• the latest released version from CRAN with
``````install.packages("brr")
``````
• the latest development version from `github` using the `devtools` package:
``````devtools::install_github('stla/brr', build_vignettes=TRUE)
``````

### Basic usage

Create a `brr` object with the `Brr` function to set the prior parameters `a`, `b`, `c`, `d`, the two Poisson counts `x` and `y` and the samples sizes (times at risk) `S` and `T` in the two groups. Simply do not set the prior parameters to use the non-informative prior:

``````model <- Brr(x=2, S=17877, y=9, T=16674)
``````

Plot the posterior distribution of the rate ratio `phi`:

``````plot(model, dpost(phi))
``````

Get credibility intervals about `phi`:

``````confint(model)
``````

Get the posterior probability that `phi>1`:

``````ppost(model, "phi", 1, lower.tail=FALSE)
``````

Update the `brr` object to include new sample sizes and get a summary of the posterior predictive distribution of `x`:

``````model <- model(Snew=10000, Tnew=10000)
spost(model, "x", output="pandoc")
``````

Look at the vignettes:

``````browseVignettes(package = "brr")
``````

### References

S. Laurent, C. Legrand: A Bayesian framework for the ratio of two Poisson rates in the context of vaccine efficacy trials. ESAIM, Probability \& Statistics 16 (2012), 375--398.

S. Laurent: Some Poisson mixtures distributions with a hyperscale parameter. Brazilian Journal of Probability and Statistics 26 (2012), 265--278.

S. Laurent: Intrinsic Bayesian inference on a Poisson rate and on the ratio of two Poisson rates. Journal of Statistical Planning and Inference 142 (2012), 2656--2671.

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brr documentation built on May 29, 2017, 3:10 p.m.