Tools to Support the Sheffield Elicitation Framework

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.


News

SHELF v1.5.0 (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.

SHELF v1.4.0 (2018-08-18)

  • 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"

SHELF v1.3.0 (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

SHELF v1.2.3 (2017-02-10)

  • 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

SHELF v1.2.2 (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

SHELF v1.2.1 (2016-09-06)

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

  • Bug fixed: plotting best fitting individual distributions for multiple experts

SHELF v1.2.0 (2016-08-16)

  • 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

SHELF v1.1.0 (2016-01-29)

  • 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

Reference manual

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install.packages("SHELF")

1.6.0 by Jeremy Oakley, 4 days ago


https://github.com/OakleyJ/SHELF


Report a bug at https://github.com/OakleyJ/SHELF/issues


Browse source code at https://github.com/cran/SHELF


Authors: Jeremy Oakley


Documentation:   PDF Manual  


GPL-2 | GPL-3 license


Imports ggplot2, grid, shiny, stats, graphics, tidyr, MASS, ggExtra, gridExtra, scales, rmarkdown, grDevices, shinyMatrix, utils, ggridges, Hmisc

Suggests testthat, knitr, GGally


See at CRAN