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

1

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

1
2
3
4
5
6
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)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.