Description Usage Arguments Details Value Examples

Calculates and summarizes the posterior distribution of mortality count.

1 2 | ```
acme.table(C = 0, Rstar = 0.2496, T = 0.174, gam = c(0.5, 0.9), I = 7,
Mmax = 200, xi = 1/2, lam = 0)
``` |

`C` |
Observed mortality count. Non-negative integer or vector. |

`Rstar` |
ACME inverse-inflation factor R*, reported by acme.summary() as "Rstar." |

`T` |
The first term in recursive calculation of Rstar, from acme.summary. |

`gam` |
Values for highest posterior density credible interval. |

`I` |
Interval length, days. |

`Mmax` |
Maximimum value for which posterior probability is calculated. |

`xi` |
First parameter of gamma prior. Default is 1/2 for Objective prior. |

`lam` |
Second parameter of gamma prior. Default is 0 for Objective prior. |

Assuming a Gamma(xi, lam) on the average daily mortality rate m, this model treats the mortality M for the current period as Poisson-distributed with mean m*I. The carcass count C will include "new" carcasses with a Bi(M,T) distribution as well as "old" carcasses (if bt > 0). For derivation of resulting conditional pdf see Wolpert (2015).

This function calls `acme.post`

but suppresses plotting.

`acme.table`

returns a table which includes ACME
estimate (M_hat), posterior mean, and highest posterior credible intervals for probabilities
as specified by the parameter gam.

1 | ```
acme.table(C=0:5,Rstar = 0.2496, T = 0.174)
``` |

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