Having fitted appropriate distributions to one or more expert's judgements
individually using the `fitdist`

command, use this command to
get quantiles and probabilities from the fitted distributions

1 2 |

`fit` |
An object of class |

`quantiles` |
A vector of desired quantiles for feedback. If this argument is left out, the default is to use the same quantiles that were elicited from the experts. |

`values` |
A vector of desired probabilities; desired values of a for reporting back fitted values of P(X<a). If this argument is left out, the default is to use the same values provided by the experts. |

`dist` |
If |

`ex` |
If |

`sf` |
The number of significant figures to be displayed in the output. |

`fitted.quantiles ` |
Fitted quantiles for each expert |

`fitted.probs ` |
Fitted probabilities for each expert |

`distributions` |
The distribution used to calculate fitted probabilities/quantiles for each expert, if feedback is given for multiple experts. |

Jeremy Oakley <j.oakley@sheffield.ac.uk>

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
## Not run:
# Two experts
# Expert 1 states P(X<30)=0.25, P(X<40)=0.5, P(X<50)=0.75
# Expert 2 states P(X<20)=0.25, P(X<25)=0.5, P(X<35)=0.75
# Both experts state 0<X<100.
v <- matrix(c(30, 40, 50, 20, 25, 35), 3, 2)
p <- c(0.25, 0.5, 0.75)
myfit <- fitdist(vals = v, probs = p, lower = 0, upper = 100)
feedback(myfit)
# Feedback P(X<60) and the tertiles
feedback(myfit, values=60, quantiles=c(0.33,0.66))
# Compare fitted tertiles for different distributions, expert 2 only
feedback(myfit, quantiles=c(0.33,0.66), ex=2)
## End(Not run)
``` |

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