R/data_swop.R

In multinomineq: Bayesian Inference for Multinomial Models with Inequality Constraints

#' Strict Weak Order Polytope for 5 Elements and Ternary Choices
#'
#' Facet-defining inequalities of the strict weak order mixture model
#' for all 10 paired comparisons of 5 choice elements {a,b,c,d,e} in a
#' 3-alternative forced-choice task (Regenwetter & Davis-Stober, 2012).
#'
#' @format A list with 3 elements:
#' \describe{
#'   \item{\code{A}: }{Matrix with inequality constraints that define a polytope via \code{A*x <= b}.}
#'   \item{\code{b}: }{vector with upper bounds for the inequalities.}
#'   \item{\code{start}: }{A point in the polytope.}
#'   \item{\code{options}: }{A vector with the number of options (=3) per item type.}
#' }
#' @template ref_regenwetter2012
#' @seealso The corresponding data set \code{\link{regenwetter2012}}.
#' @examples
#' data(swop5)
#' tail(swop5$A) # A*x <= b
#' tail(swop5$b)
#' swop5$start # inside SWOP polytope
#' swop5$options # 3 choice options per item
#'
#' # check whether point is in polytope:
#' inside(swop5$start, swop5$A, swop5$b)
#'
#' \donttest{
#' # get prior samples:
#' p <- sampling_multinom(0, swop5$options,
#'   swop5$A, swop5$b,
#'   M = 100, start = swop5$start
#' )
#' colMeans(p)
#' apply(p[, 1:5], 2, plot, type = "l")
#' }
"swop5"