Description Usage Arguments Value See Also Examples
The function calculates stochastic results for alternative assignments, assignmentbased preference relation and class cardinalities. The results are computed by sampling the space of compatible models.
1  calculateStochasticResults(problem, nrSamples = 100)

problem 
A problem to consider. 
nrSamples 
Number of samples. Use more for better quality of results. 
List with the following named elements:
assignments  n x p matrix, where n is
the number of alternatives and p is number of classes; each element
[i, j]
contains the rate of samples, for which alternative a_i
was assigned to class C_j.
The exact result can be calculated with function calculateAssignments.
preferenceRelation  n x n matrix, where n is
the number of alternatives; each element [i, j]
contains the rate
of samples, for which alternative a_i was assigned to class at least
as good as class of a_j.
The exact result can be calculated with function compareAssignments.
classCardinalities  p x (n + 1) matrix, where n
is the number of alternatives and p is number of classes; each element
[i, j]
contains the rate of samples, for which j1 alternatives
were assigned to class C_i. Note! first column corresponds to
0 elements.
The exact result can be calculated with function calculateExtremeClassCardinalities.
buildProblem
calculateAssignments
compareAssignments
calculateExtremeClassCardinalities
1 2 3 4  perf < matrix(c(2,1,1,2), 2)
problem < buildProblem(perf, 2, FALSE, c('g', 'g'), c(0, 0))
calculateStochasticResults(problem, 1000)

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