Title: Tools to Support the Sheffield Elicitation Framework (SHELF)
Description: 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 or quantile 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 additional quantiles. A graphical interface for the roulette elicitation method is also provided. For multiple experts, a weighted linear pool can be calculated.
Depends: graphics, grDevices, stats, utils, shiny

Description: 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 or quantile 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 additional quantiles. A graphical interface for the roulette elicitation
method is also provided. For multiple experts, a weighted linear pool can be
calculated. Also includes functions for eliciting beliefs about population distributions.
Imports: ggplot2, grid, shiny, stats, graphics

provides a small number of probability judgements, corresponding
form of fitted probabilities and percentiles. A graphical interface for the roulette elicitation
Suggests: testthat, knitr, rmarkdown, GGally
Imports: ggplot2, grid, shiny, stats, graphics, tidyr, MASS, ggExtra

Title: Tools to Support the Sheffield Elicitation Framework

Imports: ggplot2, grid, shiny, stats, graphics, tidyr, MASS, ggExtra,

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
gridExtra, scales, rmarkdown, grDevices, shinyMatrix, utils