| alphacut {FuzzyNumbers} | R Documentation |
Compute Alpha-Cuts
Description
If A is a fuzzy number, then its \alpha-cuts are
always in form of intervals.
Moreover, the \alpha-cuts form a nonincreasing
chain w.r.t. alpha.
Usage
## S4 method for signature 'FuzzyNumber,numeric'
alphacut(object, alpha)
Arguments
object |
a fuzzy number |
alpha |
numeric vector with elements in [0,1] |
Value
Returns a matrix with two columns (left and right alha cut bounds).
if some elements in alpha are not in [0,1], then NA
is set.
See Also
Other FuzzyNumber-method:
Arithmetic,
Extract,
FuzzyNumber-class,
FuzzyNumber,
alphaInterval(),
ambiguity(),
as.FuzzyNumber(),
as.PiecewiseLinearFuzzyNumber(),
as.PowerFuzzyNumber(),
as.TrapezoidalFuzzyNumber(),
as.character(),
core(),
distance(),
evaluate(),
expectedInterval(),
expectedValue(),
integrateAlpha(),
piecewiseLinearApproximation(),
plot(),
show(),
supp(),
trapezoidalApproximation(),
value(),
weightedExpectedValue(),
width()
Other alpha_cuts:
core(),
supp()
Examples
A <- TrapezoidalFuzzyNumber(1, 2, 3, 4)
alphacut(A, c(-1, 0.4, 0.2))