plotfit {SHELF}

Plot the fitted density function for one or more experts

Description

Plots the fitted density function for one or more experts. Can also plot a fitted linear pool if more than one expert. If plotting the density function of one expert, or the linear pool only, can also indicated desired lower and upper fitted quantiles.

Usage

plotfit(
  fit,
  d = "best",
  xl = -Inf,
  xu = Inf,
  yl = 0,
  yu = NA,
  ql = NA,
  qu = NA,
  lp = FALSE,
  ex = NA,
  sf = 3,
  ind = TRUE,
  lpw = 1,
  fs = 12,
  lwd = 1,
  xlab = "x",
  ylab = expression(f[X](x)),
  legend_full = TRUE,
  percentages = FALSE,
  returnPlot = FALSE,
  showPlot = TRUE
)

Arguments

fit

An object of class elicitation.

d

The distribution fitted to each expert's probabilities. Options are "normal", "t", "skewnormal", "gamma", "lognormal", "logt","beta", "mirrorgamma", "mirrorlognormal", "mirrorlogt" "hist" (for a histogram fit), and "best" (for best fitting)

xl

The lower limit for the x-axis. The default is the 0.001 quantile of the fitted distribution (or the 0.001 quantile of a fitted normal distribution, if a histogram fit is chosen).

xu

The upper limit for the x-axis. The default is the 0.999 quantile of the fitted distribution (or the 0.999 quantile of a fitted normal distribution, if a histogram fit is chosen).

yl

The lower limit for the y-axis. Default value is 0.

yu

The upper limit for the y-axis. Will be set automatically if not specified.

ql

A lower quantile to be indicated on the density function plot. Only displayed when plotting the density function for a single expert.

qu

An upper quantile to be indicated on the density function plot. Only displayed when plotting the density function for a single expert.

lp

For multiple experts, set lp = TRUE to plot a linear pool.

ex

If judgements have been elicited from multiple experts, but a density plot for one expert only is required, the expert to be used in the plot.

sf

The number of significant figures to be displayed for the parameter values.

ind

If plotting a linear pool, set ind = FALSE to suppress plotting of the individual density functions.

lpw

A vector of weights to be used in linear pool, if unequal weighting is desired.

fs

The font size used in the plot.

lwd

The line width used in the plot.

xlab

A string or expression giving the x-axis label.

ylab

A string or expression giving the y-axis label.

legend_full

If plotting a linear pool, set ind = TRUE for each expert to be plotted with a different colour, and ind = FALSE for each expert to be plotted with the same colour, reducing the legend size.

percentages

Set to TRUE to use percentages on the x-axis.

returnPlot

Set to TRUE to return the plot as a ggplot object.

showPlot

Set to FALSE to suppress displaying the plot.

Author(s)

Jeremy Oakley <[e-mail]>

Examples

## 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)

# Plot both fitted densities, using the best fitted distribution
plotfit(myfit)

# Plot a fitted beta distribution for expert 2, and show 5th and 95th percentiles
plotfit(myfit, d = "beta", ql = 0.05, qu = 0.95, ex = 2)


# Plot a linear pool, giving double weight to expert 1
plotfit(myfit,  lp = T, lpw = c(2,1))


# Plot a linear pool, giving double weight to expert 1, 
# show 5th and 95th percentiles, surpress plotting of individual distributions, 
# and force use of Beta distributions
plotfit(myfit, d = "beta",  lp = T, lpw = c(2,1), ql = 0.05, qu = 0.95, ind=FALSE )

## End(Not run)