R: Log posterior for a binary response model with a logistic...

logisticpost {LearnBayes} | R Documentation

## Log posterior for a binary response model with a logistic link and a uniform prior

### Description

Computes the log posterior density of (beta0, beta1) when yi are independent binomial(ni, pi) and logit(pi)=beta0+beta1*xi and a uniform prior is placed on (beta0, beta1)

### Usage

    logisticpost(beta,data)

### Arguments

`beta` | vector of parameter values beta0 and beta1
`data` | matrix of columns of covariate values x, sample sizes n, and number of successes y

### Value

value of the log posterior

### Author(s)

Jim Albert

### Examples

    x = c(-0.86,-0.3,-0.05,0.73)
    n = c(5,5,5,5)
    y = c(0,1,3,5)
    data = cbind(x, n, y)
    beta=c(2,10)
    logisticpost(beta,data)

[Package LearnBayes version 2.15 Index]