Implements various methods for eliciting a probability distribution for a single parameter from an expert or a group of experts. The expert provides a small number of probability judgements, corresponding to points on his or her cumulative distribution function. A range of parametric distributions can then be fitted and displayed, with feedback provided in the form of fitted probabilities and percentiles. For multiple experts, a weighted linear pool can be calculated. Also includes functions for eliciting beliefs about population distributions, eliciting multivariate distributions using a Gaussian copula, eliciting a Dirichlet distribution, and eliciting distributions for variance parameters in a random effects meta-analysis model. R Shiny apps for most of the methods are included.
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