GeneratorNExpUU.md
In FuzzyResampling: Resampling Methods for Triangular and Trapezoidal Fuzzy Numbers

Function returns correct values

Code
  set.seed(123456)
  GeneratorNExpUU(10, 0, 1, 1, 1, 2)
Output
              [,1]       [,2]        [,3]      [,4]
   [1,] -1.3359262 -0.8293096  1.32736059 2.3828154
   [2,] -3.5080725 -2.6458133 -0.06523875 0.2980204
   [3,] -2.5620562 -1.8024989  1.54394081 1.8394103
   [4,] -2.6384334 -1.6740501  0.95848757 2.1404356
   [5,]  0.2391184  1.0735556  2.28296076 2.2889409
   [6,] -0.1176306  0.7194064  1.92628139 2.6483136
   [7,]  0.9990109  1.2664780  1.66876078 1.9272962
   [8,]  2.2441723  2.4201048  3.64385733 3.6730154
   [9,]  0.3242936  0.5203293  2.19960875 2.5884698
  [10,] -2.8096190 -2.7900388  0.07154642 1.3688878

Code
  set.seed(123456)
  GeneratorNExpUU(5, 0, 1, 1, 1, 2, increases = TRUE)
Output
            [,1]        [,2]     [,3]      [,4]
  [1,] 0.4777778  0.23775491 1.388146 0.3319750
  [2,] 0.7005048 -0.46363582 1.386995 1.0459375
  [3,] 0.8798891 -0.96555960 2.014764 1.7382564
  [4,] 0.8777937 -0.04948244 1.534984 0.4623134
  [5,] 0.8538796  1.21913415 4.013793 0.2381618

Code
  set.seed(123456)
  GeneratorNExpUU(10, -2, 1.4, 2.5, 1.5, 2.5)
Output
              [,1]       [,2]        [,3]        [,4]
   [1,] -2.2579155 -1.4979907 -0.63532260  0.68399590
   [2,] -4.6277618 -3.3343731 -2.30214327 -1.84806935
   [3,] -4.2153373 -3.0760014 -1.73742552 -1.36808865
   [4,] -4.0287075 -2.5821326 -1.52911755 -0.05168251
   [5,] -0.5699779  0.6816780  1.16544004  1.17291521
   [6,] -2.1333327 -0.8777773 -0.39502731  0.50751294
   [7,] -0.5821939 -0.1809933 -0.02008018  0.30308907
   [8,]  1.2067886  1.4706873  1.96018834  1.99663596
   [9,] -0.9176901 -0.6236365  0.04807524  0.53415151
  [10,] -3.5715514 -3.5421811 -2.39754701 -0.77587030

Code
  set.seed(123456)
  GeneratorNExpUU(10, -2, 1.4, 3, 0, 0, increases = TRUE)
Output
        [,1]       [,2]        [,3] [,4]
   [1,]    0 -1.3871212 -0.66823109    0
   [2,]    0 -3.1763887 -2.31619721    0
   [3,]    0 -2.9795016 -1.86402169    0
   [4,]    0 -2.4646968 -1.58718423    0
   [5,]    0  0.7602580  1.16339303    0
   [6,]    0 -0.8701071 -0.46781540    0
   [7,]    0 -0.1779308 -0.04383653    0
   [8,]    0  1.4761900  1.88410755    0
   [9,]    0 -0.5804430 -0.02068322    0
  [10,]    0 -3.3845895 -2.43072781    0

Code
  set.seed(123456)
  GeneratorNExpUU(n = 10, mu = 0.5, sigma = 1, lambda = 0.5, b = 1, c = 2)
Output
              [,1]       [,2]      [,3]     [,4]
   [1,] -2.4989690 -1.9923524 2.3209880 3.376443
   [2,] -5.3778380 -4.5155789 0.6455703 1.008829
   [3,] -3.5095532 -2.7499960 3.9428835 4.238353
   [4,] -3.8999709 -2.9355877 2.3294877 3.511436
   [5,] -0.4395817  0.3948556 2.8136658 2.819646
   [6,]  0.2673156  1.1043526 3.5181027 4.240135
   [7,]  1.4530734  1.7205405 2.5251060 2.783641
   [8,]  2.6616317  2.8375642 5.2850693 5.314227
   [9,]  0.1763912  0.3724268 3.7309858 4.119847
  [10,] -4.6734922 -4.6539120 1.0692584 2.366600

Code
  set.seed(123456)
  GeneratorNExpUU(n = 10, mu = 0.5, sigma = 1, lambda = 0.5, b = 1, c = 2,
    increases = TRUE)
Output
              [,1]       [,2]      [,3]       [,4]
   [1,] 0.50661655 -1.9923524 2.3209880 1.05545480
   [2,] 0.86225915 -4.5155789 0.6455703 0.36325914
   [3,] 0.75955726 -2.7499960 3.9428835 0.29546949
   [4,] 0.96438325 -2.9355877 2.3294877 1.18194804
   [5,] 0.83443724  0.3948556 2.8136658 0.00598014
   [6,] 0.83703693  1.1043526 3.5181027 0.72203220
   [7,] 0.26746709  1.7205405 2.5251060 0.25853540
   [8,] 0.17593249  2.8375642 5.2850693 0.02915810
   [9,] 0.19603568  0.3724268 3.7309858 0.38886101
  [10,] 0.01958019 -4.6539120 1.0692584 1.29734137