Description Usage Arguments Value See Also Examples
The function calculates stochastic results for alternative assignments, assignment-based 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 j-1 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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