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

Function returns correct values

Code
  set.seed(123456)
  GeneratorNU(10, 0, 1, 1, 2)
Output
              [,1]        [,2]       [,3]      [,4]
   [1,]  0.2232752  0.67413962  1.3567019 2.0258168
   [2,] -1.8358833 -0.35669302  0.5930804 2.0907924
   [3,] -2.2787371 -0.48765218 -0.1238451 0.8893880
   [4,] -0.6733445 -0.08441797  0.2065683 1.9310866
   [5,]  0.7437729  1.77447789  3.0762070 4.5953215
   [6,] -0.7353437  0.13395536  0.9147371 2.8435036
   [7,] -0.7178038  0.43252645  2.2647786 3.9336531
   [8,]  0.1429397  1.62485173  3.3742628 5.0483366
   [9,] -1.0419931  0.31435215  1.8803856 2.4153197
  [10,] -1.3161855 -0.59215309  0.1792389 0.5311039

Code
  set.seed(123456)
  GeneratorNU(5, 0, 1, 1, 2, increases = TRUE)
Output
            [,1]        [,2]       [,3]     [,4]
  [1,] 0.3191871  0.03574404  1.7296895 1.401010
  [2,] 0.1612905 -0.86984180  0.6025956 1.759778
  [3,] 0.2653007 -1.26031185 -0.1573961 1.755587
  [4,] 0.3438108 -0.79336122  0.4224810 1.707759
  [5,] 0.9555557  1.25841918  3.0294620 0.331975

Code
  set.seed(123456)
  GeneratorNU(8, -1, 2, 1.3, 2.1)
Output
              [,1]       [,2]       [,3]      [,4]
  [1,] -0.96019906 -0.4747700  1.2885775 1.7619851
  [2,] -2.05905292 -1.8089830 -0.6414393 0.9117104
  [3,] -3.87579293 -2.1454954 -0.5661479 1.3144912
  [4,] -2.00397502 -1.8353934  0.3161066 0.9344794
  [5,]  1.29707740  3.2970398  4.6145549 5.6967952
  [6,] -1.26631503  0.5640814  0.8847040 1.7974681
  [7,] -0.04313745  1.4523856  2.3046904 3.5125372
  [8,]  2.51046432  3.7818138  5.1351575 6.6911651

Code
  set.seed(123456)
  GeneratorNU(5, 0, 1, 1, 2, increases = FALSE)
Output
             [,1]        [,2]       [,3]     [,4]
  [1,] -0.2834431  0.03574404  1.7296895 3.130699
  [2,] -1.0311323 -0.86984180  0.6025956 2.362374
  [3,] -1.5256125 -1.26031185 -0.1573961 1.598191
  [4,] -1.1371720 -0.79336122  0.4224810 2.130240
  [5,]  0.3028635  1.25841918  3.0294620 3.361437

Code
  set.seed(123456)
  GeneratorNU(n = 5, mu = 1.5, sigma = 1.5, a = 1.5, b = 2, increases = FALSE)
Output
              [,1]       [,2]     [,3]     [,4]
  [1,]  1.23442895  1.5536161 4.094534 5.495544
  [2,]  0.03394680  0.1952373 2.403893 4.163671
  [3,] -0.65576845 -0.3904678 1.263906 3.019493
  [4,] -0.03385263  0.3099582 2.133722 3.841481
  [5,]  2.43207310  3.3876288 6.044193 6.376168

Code
  set.seed(123456)
  GeneratorNU(n = 5, mu = 1.5, sigma = 1.5, a = 0, b = 0, increases = FALSE)
Output
            [,1]      [,2]      [,3]      [,4]
  [1,] 2.7505998 2.7505998 2.7505998 2.7505998
  [2,] 1.0859283 1.0859283 1.0859283 1.0859283
  [3,] 0.9674972 0.9674972 0.9674972 0.9674972
  [4,] 1.6312311 1.6312311 1.6312311 1.6312311
  [5,] 4.8783836 4.8783836 4.8783836 4.8783836