Description Usage Arguments Value Author(s) Examples

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)

1 |

`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 of the log posterior

Jim Albert

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