---
title: "README"
author: "ddd"
date: "March 19, 2017"
output: pdf_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## multicmp

multicmp is a toolkit containing statistical analysis models motivated by multivariate forms of the Conway-Maxwell-Poisson (COM-Poisson) distribution for flexible modeling of multivariate count data, especially in the presence of data dispersion, via the bivariate COM-Poisson distribution described in [Sellers et al. (2016)](http://dx.doi.org/10.1016/j.jmva.2016.04.007). Currently the package only supports bivariate data. Future development will extend the package to higher-dimensional data.

Note that multicmp references _bivpois_ package (Karlis and Ntzoufras).

To use multicmp, one will first need to install the following two packages:

```R
  install.packages("numDeriv")
  install.packages("stats")
````

One can install the latest released version of multicmp from CRAN with:

```R
  install.packages("multicmp")
````

## Using multicmp

To get started with multicmp right away, see the parameter estimation below.
For a more detailed and technical description of the bivariate COM-Poisson distribution, see [Sellers et al. (2016)](http://dx.doi.org/10.1016/j.jmva.2016.04.007).

The multicmp package houses the _accidents_ data set (Arbous and Kerrich, 1951)

```{r, echo=FALSE}
# helper loading to be hidden

library(numDeriv)
load("data/accidents.rdata")
source('R/multicmpests.R')

````


```R
  data(accidents)
````

```{r}

multicmpests(accidents)

`````