biv.betab {repeated}R Documentation

Bivariate Beta-binomial Regression Models

Description

biv.betab fits dependent (logit) linear regression models to a bivariate beta-binomial distribution.

Usage

biv.betab(freq, x=NULL, p, depend=TRUE, print.level=0,
        typsiz=abs(p), ndigit=10, gradtol=0.00001, stepmax=10*sqrt(p%*%p),
        steptol=0.00001, iterlim=100, fscale=1)

Arguments

freq A matrix containing four columns corresponding to 00, 01, 10, and 11 responses.
x A matrix of explanatory variables, containing pairs of columns, one for each response, and the same number of rows as freq.
p Initial parameter estimates: intercept, dependence (if depend is TRUE, and one for each pair of columns of x.
depend If FALSE, the independence (logistic) model is fitted.
other Arguments for nlm.

Value

A list of class bivbetab is returned.

Author(s)

J.K. Lindsey

Examples

y <- matrix(  c( 2, 1, 1,13,
                 4, 1, 3, 5,
                 3, 3, 1, 4,
                15, 8, 1, 6),ncol=4,byrow=TRUE)
first <- c(0,0,1,1)
second <- c(0,1,0,1)
self <- cbind(first,second)
other <- cbind(second,first)
biv.betab(y,cbind(self,other),p=c(-1,2,1,1))
# independence
biv.betab(y,cbind(self,other),p=c(-1,1,1),dep=FALSE)

[Package repeated version 1.0 Index]