Description Usage Arguments Details Value Examples

Report the median and 100(1-alpha)% credible interval for point on the population CDF

1 2 3 4 5 6 7 8 9 10 | ```
cdffeedback(
medianfit,
precisionfit,
quantiles = c(0.05, 0.95),
vals = NA,
alpha = 0.05,
median.dist = "best",
precision.dist = "gamma",
n.rep = 10000
)
``` |

`medianfit` |
The output of a fitdist command following elicitation of the expert's beliefs about the population median. |

`precisionfit` |
The output of a fitprecision command following elicitation of the expert's beliefs about the population precision. |

`quantiles` |
A vector of quantiles |

`vals` |
A vector of population values |

`alpha` |
The size of the 100(1-alpha)% credible interval |

`median.dist` |
The fitted distribution for the population median. Can be one of |

`precision.dist` |
The fitted distribution for the population precision. Can either be |

`n.rep` |
The number of randomly sampled CDFs used to estimated the median and credible interval. |

Denote the uncertain population CDF by

*P(X ≤ x | μ, σ^2),*

where *μ*
is the uncertain population median and *σ^(-2)* is the uncertain population precision.
Feedback can be reported in the form of the median and 100(1-alpha)% credible interval for
(a) an uncertain probability *P(X ≤ x | μ, σ^2)*, where *x* is a specified
population value and (b) an uncertain quantile *x_q* defined by *P(X ≤ x_q | μ, σ^2) = q*, where *q* is a specified
population probability.

Fitted median and 100(1-alpha)% credible interval for population quantiles and probabilities.

`$quantiles` |
Each row gives the fitted median
and 100(1-alpha)% credible interval for each uncertain population quantile
specified in |

`$probs` |
Each row gives the fitted median
and 100(1-alpha)% credible interval for each uncertain population probability
specified in |

1 2 3 4 5 6 7 | ```
## Not run:
prfit <- fitprecision(interval = c(60, 70), propvals = c(0.2, 0.4), trans = "log")
medianfit <- fitdist(vals = c(50, 60, 70), probs = c(0.05, 0.5, 0.95), lower = 0)
cdffeedback(medianfit, prfit, quantiles = c(0.01, 0.99),
vals = c(65, 75), alpha = 0.05, n.rep = 10000)
## End(Not run)
``` |

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