# CV: Coefficient of variation for n PLFNs In Sim.PLFN: Simulation of Piecewise Linear Fuzzy Numbers

## Description

This function is able to calculate the coefficient of variation (CV) of a sample from Piecewise Linear Fuzzy Numbers (PLFNs).

## Usage

 `1` ```CV(S.PLFN) ```

## Arguments

 `S.PLFN` A sample from Piecewise Linear Fuzzy Numbers (PLFNs), with n PLFNs. This sample is an array with ` dim=c(knot.n+2,2,n) `.

## Value

This function returned a Piecewise Linear Fuzzy Number as the coefficient of variation of several PLFNs.

## See Also

DISTRIB FuzzyNumbers FuzzyNumbers.Ext.2 Calculator.LR.FNs

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25``` ```library(FuzzyNumbers) n=3; knot.n=4 Sample <- S.PLFN( n, knot.n, X.dist="norm", X.dist.par=c(3,2), slX.dist="exp", slX.dist.par=3, srX.dist="beta", srX.dist.par=c(1,3) ) Sample # For plotting random fuzzy sample: xlim = c(0, max(Sample[knot.n+2,2,])) plot( cuts.to.PLFN(Sample[,,1]), type="b", xlim=xlim ) plot( cuts.to.PLFN(Sample[,,2]), type="b", add=TRUE ) plot( cuts.to.PLFN(Sample[,,3]), type="b", add=TRUE ) abline( h=round((knot.n+1):0/(knot.n+1),4), lty=3, col="gray70") FuzzyNumbers::plot(Mean(Sample), col=4, lwd=2, add=TRUE, type="b") plot(Var(Sample), col=3, lwd=2, add=TRUE, type="b") plot(Sd(Sample), col=6, lwd=2, add=TRUE, type="b") CV = CV(Sample) CV PLFN.to.cuts(CV, knot.n) plot(CV, col=2, lwd=2, add=TRUE, type="b") ```

Sim.PLFN documentation built on May 2, 2019, 5:51 a.m.