Description Usage Arguments Value Author(s) Examples

Computes probability intervals for the log precision parameter K in a beta-binomial model for all "leave one out" models using sampling importance resampling

1 | ```
bayes.influence(theta,data)
``` |

`theta` |
matrix of simulated draws from the posterior of (logit eta, log K) |

`data` |
matrix with columns of counts and sample sizes |

`summary` |
vector of 5th, 50th, 95th percentiles of log K for complete sample posterior |

`summary.obs` |
matrix where the ith row contains the 5th, 50th, 95th percentiles of log K for posterior when the ith observation is removed |

Jim Albert

1 2 3 4 5 6 | ```
data(cancermortality)
start=array(c(-7,6),c(1,2))
fit=laplace(betabinexch,start,cancermortality)
tpar=list(m=fit$mode,var=2*fit$var,df=4)
theta=sir(betabinexch,tpar,1000,cancermortality)
intervals=bayes.influence(theta,cancermortality)
``` |

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