New app elicitSurvivalExtrapolation() and supporting functions survivalScenario(), survivalModelExtrapolations() for eliciting extrapolated survival probabilities.

vignette multivariate-normal-copula removed.

Added the skew normal distribution to the set of fitted distributions.

Bug fixed in feedback - was forcing rounding to 3 s.f. if using feedback for multiple experts.

elicitQuartiles() and elicitTertiles() are deprecated. Use elicit() instead.

condDirichlet() is deprecated. Use elicitDirchlet() instead.

elicitConcProb() is deprecated. Use elicitBivariate() instead.

non-exported function extractDistributions() removed.

package test coverage improved.

elicitation report includes roulette allocation, if used.

improved error handling in shiny apps.

Changed multivariate normal sampling in copulaSample() to use Cholesky decomposition instead of eigendecomposition (latter can produce different results on different machines).

new function compareGroupRIO(). Use this to produce plots to compare the the final consensus (“RIO”) distribution with the individual elicited judgements, and a linear pool of the individual elicited judgements. Incorporated this feature in the elicit() app.

can now fit exponential distributions as a special case of the Gamma distribution (or mirror exponential as special case of mirror gamma). Only requires one appropriate limit and a single probability. Mainly intended for the roulette method, if probs are only allocated to two adjacent bins. Updated error reporting when fitdist() is unable to fit distributions.

bug fixed: output names from feedback() were different depending on whether single or multiple experts. Changed to be consistent with single expert case.

optional input arguments added to elicit() to allow roulette options to be specified from command line.

bug fixed: copulaSample() will now run if fitdist() was used on separate judgements from multiple experts. Extra argument (ex) used to select judgements from a single expert (copulaSample() will not produce judgements for multiple experts simultaneously).

new package test for copulaSample()

some internal naming changes in fitdist(): tParameters, fFit, tError. (Sorry, my naming formatting is all over the place…)

argument int removed from plotfit(): can no longer launch shiny apps from the plotfit() command for plotting distributions. Use elicit() and elicitMultiple() instead for interactive plotting.

elicitation report files (R Markdown documents) now include plots of fitted distributions.

Bugs fixed in elicitDirichlet() - code wouldn’t run with more than three categories.

fitdist() has a new argument for excluding log t and mirror log t when identifying best fit (default is FALSE).

Plots can be downloaded from shiny apps as .png files.

New (negatively skewed) distributions: mirror gamma, mirror lognormal, and mirror log t. These all fit distributions to (upper - X).

Better handling of expert names: elicitMultiple(): can now click on and edit expert names; names are displayed in all plots. plotfit() will now use the expert names, if provided in fitdist(). Can also specify names in plotTertiles() and plotQuartiles().

elicitMultiple(): can now control axes limits in quartile and tertile plot.

new function rlinearpool() for sampling from a weighted linear pool

bug fixed in copulaSample. Was rounding samples to 3 s.f. Increased to 8. Mistake in help file corrected, regarding syntax for distribution names.

elicitExtension(): can now upload a sample from the distribution of the extension variable, instead of eliciting a distribution.

plotfit(): additional argument returnPlot (default is FALSE) will also return the plot as a ggplot object.

new app for the extension method: elicitMixture(), for discrete extension variables.

bug fixed in elicitExtension(): when plotting conditional densities for the logit link function, x-axis limits now restricted to 0 and 1.

bug fixed in plotfit(): will now correctly display a single distribution for a selected expert when requested, if multiple distributions have been elicited.

plinearpool() and qlinearpool(): can now directly specify different distribution types for each expert to use in the linear pool.

fitdist(): extra argument expertnames, for specifying row names in the various outputs.

elicit() app: can now report fitted probabilities as well as fitted quantiles, and can change x-axis label

bug fixed: switched from class(x) == “foo” to inherits(x, “foo”), to avoid assumption length(class(x)) == 1

new app for the extension method: elicitExtension(). New command line functions for the extension method are plotConditionalDensities(), plotConditionalMedianFunction() and sampleMarginalFit().

makeCDFPlot() function is now exported: plots the elicited cumulative probabilities, and fitted cumulative distribution functions.

elicitMultiple() app: can now enter judgements with the roulette method, and save/load judgements as .csv files

column names changed in output of feedback(), fitdist() and sampleFit() to be consistent: “normal”, “t”, “gamma”, “lognormal”, “logt”, “beta”, “hist”

roulette() has been removed, and the roulette method is now available within elicit()

Extra argument percentages in plotfit() and plotTertiles() for using percentage scale on x-axis

New function sampleFit(), for generating samples from fitted distributions.

Minor change to fitDirichlet(), to allow marginal elicitation fits to be specified as a single list.

Update to fitprecision(): interval used in the proportion method can now be a tail area of the population distribution

New shiny app elicitBivariate() for eliciting bivariate distributions using a Gaussian copula

Significant update to elicit() shiny app: can now switch between multiple methods within the same app

New shiny app elicitMultiple() for fitting individual distributions to multiple experts’ judgements

Bugs fixed: plinearpool() now chooses the best fitting distribution for each expert if argument d = “best” is specified. Correctly handles probabilities for log-t, where x is below lower limit.

Bugs fixed: qlinearpool() could return NA in some cases if argument d = “best” was specified: now fixed. Correctly handles probabilities for log-t, where x is below lower limit. Minor improvement to accuracy in estimated quantiles: finer grid used in linear interpolation of the quantile function.

New function: generateReport(): renders an Rmarkdown document to give formulae and parameter values for all the fitted distributions

New function: condDirichlet(), for viewing conditional distributions from elicited Dirichlet distributions

New functions: plotQuartiles() and plotTertiles(), for displaying individuals quartiles/tertiles elicited from a group of experts

New functions: elicitQuartiles() and elicitTertiles(): shiny apps for eliciting with the quartile and tertile methods

elicit() and roulette() functions now both return the elicited values and results as objects of class “elicitation”

Bug fixed: ensure solid line used for linear pool when plotting. Option in plotfit added to plot all individual densities with same colour, to simplify legend.

New function: linearPoolDensity, for extracting density values from the linear pool.

Bug fixed: can now accept more than 26 experts.

Bug fixed: qlinearpool/plinearpool now works with log t distributions.

New function: elicitHeterogen, for eliciting prior for variance of random effects in meta-analysis

Bug fixed: can fit (and plot) distributions bounded below when lower limit is negative

Bug fixed: roulette method shiny interface works with non-integer bin boundaries

Accept non-decreasing probabilities in elicited judgements, rather than only strictly increasing probabilities

Can specify own axes labels in the plotfit command with arguments xlab and ylab

Update to Multivariate-normal-copula.Rmd vignette, to match update to GGally

Bug fixed: interactive plots now work for plotting individual distributions for multiple experts

Bug fixed: plotting best fitting individual distributions for multiple experts

Roulette elicitation method now implemented using shiny

New functions fitDirchlet and feedbackDirichlet for eliciting Dirichlet distributions

New functions copulaSample and elicitConcProb for eliciting dependent distributions using multivariate normal copulas

New function compareIntervals for comparing fitted intervals for individual distributions from multiple experts

Change to expert.names from numbers to letters in fitdist

Vignettes added: overview of SHELF, eliciting a Dirichlet distribution, eliciting a bivariate distribution with a bivariate normal copula

Change in fitdist to starting values in optimisation: will now check for exact fits if only two probabilities elicited

New functions added for eliciting beliefs about uncertain population distributions: cdffeedback, cdfplot, fitprecision, pdfplots