multinbmod (version 1.0)

multinbmod-package: Regression analysis of overdispersed correlated count data

Description

This is a robust likelihood approach for the regression analyis of overdispersed correlated counts data with cluster varying covariates. The approach fits a multivariate negative binomial model by maximum likelihood and provides robust estimates of the regression coefficients.

Details

Package:

multinbmod

Type:

Package

Version:

1.0

Date:

2014-01-14

License:

GPL-2

LazyLoad:

yes

Use function multinbmod to fit a multivariate negative binomial model by maximum likelihood. Robust estimates of regression parameters are provided.

References

Solis-Trapala, I.L. and Farewell, V.T. (2005) Regression analysis of overdispersed correlated count data with subject specific covariates. Statistics in Medicine, 24: 2557-2575.

Examples

id <- factor(rep(1:20, rep(5, 20)))
y <- rnbinom(100, mu = rexp(100,1)+rep(rexp(20,.3),rep(5,20)),size=2.5)
x<-rbinom(100,1,.5)
dat <- data.frame(y = y, x = x, id = id)
multinbmod(y~x,data=dat,id=id)
summary(multinbmod(y~x,data=dat,id=id))