Changes in version 1.13.0 (2026-04-04) - new tabs in survivalModelExtrapolations() for eliciting RIO judgements and comparing RIO to individual judgements - new app elicitSHELF() for implementing the main SHELF protocol (individual and RIO judgements) in one app - both survivalModelExtrapolations() and elicitSHELF() include new visualisation for eliciting RIO judgemetns, based on roulette - solver argument changed in sn::qsn() to make feedback more robust Changes in version 1.12.1 (2025-11-17) - bug fixed in survivalModelExtrapolations() when using tOffset argument Changes in version 1.12.0 (2025-03-01) - bug fixed in survivalModelExtrapolations() - additional supporting functions for elicitSurvivalExtrapolation() available as standalone functions: surivivalExtrapolatePlot() and makeSurvivalTable() - functions for survival extrapolation updated to handle weighted observations Changes in version 1.11.0 (2024-09-06) - New app elicitSurvivalExtrapolation() and supporting functions survivalScenario(), survivalModelExtrapolations() for eliciting extrapolated survival probabilities. - vignette multivariate-normal-copula removed. Changes in version 1.10.0 (2024-05-07) - 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. Changes in version 1.9.0 (2023-06-07) - 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...) Changes in version 1.8.0 (2021-06-18) - 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. Changes in version 1.7.0 (2020-02-08) - 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 Changes in version 1.6.0 (2019-06-14) - 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" Changes in version 1.5.0 (2019-03-26) - 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. Changes in version 1.4.0 (2018-08-16) - 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" Changes in version 1.3.0 (2017-10-31) - 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 Changes in version 1.2.3 (2017-02-11) - 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 Changes in version 1.2.2 (2016-11-14) - 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 Changes in version 1.2.1 (2016-10-03) - Bug fixed: interactive plots now work for plotting individual distributions for multiple experts - Bug fixed: plotting best fitting individual distributions for multiple experts Changes in version 1.2.0 (2016-08-17) - 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 Changes in version 1.1.0 (2016-02-05) - 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