Report quantiles and probabilities from the fitted probability distributions

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Description

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

Usage

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feedback(fit, quantiles = NA, values = NA, dist = "best", ex = NA,
  sf = 3)

Arguments

fit

An object of class elicitation.

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 fit contains judgements from multiple experts, dist is distribution to be used for calculating probabilities and quantiles. Options are "normal", "t", "gamma", "lognormal", "logt", "beta", or "best". The default option, "best", uses the best fitting distribution for each expert.

ex

If fit contains judgements from multiple experts, specifying a value for ex will select a single expert for feedback. Note that for a single expert, feedback is given for all suitable types of distribution, but for multiple experts, feedback is given for one type of distribution only.

sf

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

Value

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.

Author(s)

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

Examples

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## 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)