This function takes in a matrix of Markov chain Monte Carlo (MCMC) samples from a ‘carbayes’ model object, such as a set of parameters or fitted values, and calculates posterior quantiles and exceeedence probabilities. The latter are probabilities of the form P(quantity > c|data), where c is a threshold chosen by the user.

1 | ```
summarise.samples(samples, columns=NULL, quantiles=0.5, exceedences=NULL)
``` |

`samples` |
A matrix of MCMC samples obtained from a ‘carbayes’ model object. |

`columns` |
A vector of column numbers stating which columns in the matrix of MCMC samples summaries are required for. Defaults to all columns. |

`quantiles` |
The vector of posterior quantiles required. |

`exceedences` |
The vector of threshold levels, c, that exceedence probabilities are required for. |

`quantiles ` |
A 2 dimensional array containing the requied posterior quantiles. Each row relates to a parameter and each column to a different requested quantile. |

`exceedences ` |
A 2 dimensional array containing the requied exceedence probabilities. Each row relates to a parameter, and each column to a different requested exceedence probability. |

Duncan Lee

1 | ```
## See the vignette accompanying this package for an example of its use.
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.