Description Usage Arguments Value References See Also Examples

This function is able to produce / simulate a random sample from Piecewise Linear Fuzzy Numbers (PLFNs).

1 2 |

`n` |
the size of random sample of PLSNs. |

`knot.n` |
the number of knots; see package |

`type` |
The possible values of this argument is |

`X.dist` |
The distribution name of the random variable (for simulate the core of random fuzzy number) is determined by characteristic element |

`X.dist.par` |
A vector of distribution parameters (for simulate the core of random fuzzy number) with considered ordering in |

`slX.dist` |
The distribution name of the random variable (for simulate the left spread value of random fuzzy number) is determined by characteristic element |

`slX.dist.par` |
A vector of distribution parameters (for simulate the left spread value of random fuzzy number) with considered ordering in |

`srX.dist` |
The distribution name of the random variable (for simulate the right spread value of random fuzzy number) is determined by characteristic element |

`srX.dist.par` |
A vector of distribution parameters (for simulate the right spread value of random fuzzy number) with considered ordering in |

Considering the `type`

argument, this function returned/simulate/create one of following fuzzy numbers:
(1) Triangular Fuzzy Number,
(2) Trapezoidal Fuzzy Number,
(3) Piecewise Linear Fuzzy Number, and
(4) Piecewise Linear Fuzzy Interval.

Gagolewski, M., Caha, J. (2015) FuzzyNumbers Package: Tools to deal with fuzzy numbers in R. R package version 0.4-1, https://cran.r-project.org/web/packages=FuzzyNumbers

Gagolewski, M., Caha, J. (2015) A guide to the FuzzyNumbers package for R (FuzzyNumbers version 0.4-1) http://FuzzyNumbers.rexamine.com

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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ```
library(FuzzyNumbers)
# Let x ~~ ( X~N(0,1) ; s_X^l~Exp(3) ; s_X^r~beta(1,3) )
n=3; knot.n=3
Sam <- S.PLFN( n=3, knot.n=4, type="Tra",
X.dist="norm", X.dist.par=c(0,1),
slX.dist="exp", slX.dist.par=3,
srX.dist="beta", srX.dist.par=c(1,3)
)
Sam
Sam[,,"X3"]
# For plotting random fuzzy sample:
xlim = c( min(Sam), max(Sam) )
plot( cuts.to.PLFN(Sam[,,1]), type="b", col=1, xlim=xlim )
plot( cuts.to.PLFN(Sam[,,2]), type="b", col=2, add=TRUE )
plot( cuts.to.PLFN(Sam[,,3]), type="b", col=3, add=TRUE )
abline( h=round((knot.n+1):0/(knot.n+1),4), lty=3, col="gray70")
``` |

```
, , X1
L U
1 -0.3773801 0.2012215
0.8 -0.3939854 0.2013899
0.6 -0.4105907 0.2015582
0.4 -0.4271960 0.2017266
0.2 -0.4438013 0.2018949
0 -0.4604066 0.2020633
, , X2
L U
1 -2.647724 -0.3366846
0.8 -2.723382 -0.2966154
0.6 -2.799041 -0.2565462
0.4 -2.874699 -0.2164770
0.2 -2.950358 -0.1764078
0 -3.026016 -0.1363386
, , X3
L U
1 -0.7625111 -0.15660038
0.8 -0.8375531 -0.11108919
0.6 -0.9125950 -0.06557800
0.4 -0.9876370 -0.02006681
0.2 -1.0626789 0.02544439
0 -1.1377209 0.07095558
L U
1 -0.7625111 -0.15660038
0.8 -0.8375531 -0.11108919
0.6 -0.9125950 -0.06557800
0.4 -0.9876370 -0.02006681
0.2 -1.0626789 0.02544439
0 -1.1377209 0.07095558
```

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