% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/FuzzySeparationProbabilistic.R
\name{FuzzySeparationProbabilistic}
\alias{FuzzySeparationProbabilistic}
\title{Fuzzy Separation matrix computation with Product t-norm and Probabilistic-sum t-conorm}
\usage{
FuzzySeparationProbabilistic(dom, type, ...)
}
\arguments{
\item{dom}{square matrix representing the dominance degrees between pairs of poset elements. Columns and rows names of `dom`
are interpreted as the labels of the poset elements. `dom` can be computed by using functions such as `BLSDominance`,
`BubleyByesMRP` and `ExactMRP`.}

\item{type}{type of fuzzy separation to be computed. Possible choices are:
"symmetric", "asymmetricLower", "asymmetricUpper", "vertical", "horizontal".
For details on the definition of symmetric, asymmetric, vertical and horizontal separations see Fattore et al. (2024).}

\item{...}{additional types of fuzzy separations to be computed. Possible choices are:
"symmetric", "asymmetricLower", "asymmetricUpper", "vertical", "horizontal".}
}
\value{
list of required fuzzy separation matrices.
}
\description{
Starting from a poset dominance matrix, computes fuzzy Separation matrices by using Product t-norm and Probabilistic-sum t-conorm
}
\examples{
el <- c("a", "b", "c", "d")

dom_list <- matrix(c(
  "a", "b",
  "c", "b",
  "b", "d"
), ncol = 2, byrow = TRUE)

pos <- POSet(elements = el, dom = dom_list)

BLS <- BLSDominance(pos)

FSep <- FuzzySeparationProbabilistic(BLS, type="symmetric", "asymmetricLower", "vertical")

}
\references{
Fattore, M., De Capitani, L., Avellone, A., and Suardi, A. (2024).
A fuzzy posetic toolbox for multi-criteria evaluation on ordinal data systems.
Annals of Operations Research, https://doi.org/10.1007/s10479-024-06352-3.
}
