R：我有一个填充了随机数的矩阵，但最后一列包含所有最大值

Question

我有一个矩阵，有 30 行和 4 列，每行填充了从 0 到小于/等于 100 的随机数。

最后（第四）列包含 0 到 100 范围内的所有最大数字（即 99、98 等）。我想让数字真正分布在矩阵中，也就是说，一些最大的数字在第一列或第二列或第三列，而不仅仅是在第四列。

在获得其他 Stackexchange 贡献者的帮助后，这是我一直在使用的函数：

y <- t(replicate(30,{x <- runif(3); y <- c(x, 100 - sum(x)); sort(y/sum(y) * 100)}))

这给了我以下矩阵：

          [,1]      [,2]      [,3]     [,4]
 [1,] 0.106034080 0.8035997 0.9161168 98.17425
 [2,] 0.013372771 0.4416418 0.5053132 99.03967
 [3,] 0.477705091 0.7248394 0.7254909 98.07196
 [4,] 0.080764396 0.3859276 0.3968179 99.13649
 [5,] 0.699455094 0.7579722 0.7875055 97.75507
 [6,] 0.372264415 0.3772728 0.6589921 98.59147
 [7,] 0.114169686 0.2029357 0.4566677 99.22623
 [8,] 0.478831699 0.7960539 0.9740272 97.75109
 [9,] 0.032629269 0.2068012 0.6521174 99.10845
[10,] 0.349337576 0.3886265 0.9551120 98.30692
[11,] 0.437791360 0.4712769 0.5487138 98.54222
[12,] 0.137317329 0.6110274 0.9769346 98.27472
[13,] 0.314229467 0.4457654 0.8379763 98.40203
[14,] 0.038342032 0.3210214 0.4811107 99.15953
[15,] 0.063934371 0.5945270 0.7108552 98.63068
[16,] 0.176338974 0.3944489 0.6910675 98.73814
[17,] 0.174552999 0.6164661 0.8115936 98.39739
[18,] 0.358101562 0.6727262 0.8580072 98.11117
[19,] 0.097051604 0.1425019 0.8777943 98.88265
[20,] 0.287638218 0.5643593 0.7917288 98.35627
[21,] 0.060074348 0.1993140 0.8502848 98.89033
[22,] 0.136792340 0.1833376 0.2811030 99.39877
[23,] 0.274043764 0.5373264 0.7441432 98.44449
[24,] 0.040409521 0.5162444 0.5339423 98.90940
[25,] 0.481989448 0.5592237 0.9305969 98.02819
[26,] 0.008124932 0.6241172 0.8474349 98.52032
[27,] 0.134700798 0.3691278 0.4193065 99.07686
[28,] 0.228018480 0.5125451 0.9561445 98.30329
[29,] 0.155826657 0.6548732 0.7902131 98.39909
[30,] 0.080001684 0.4109359 0.7645531 98.74451

有没有办法让这个矩阵中的数字真正分散，而不是所有最大的数字都限制在第四列？

Answer 1

根据您之前在本网站上的问题，我相信您希望行总和为 100。如果是这种情况，您可以执行以下操作 -

apply(y, 1, sample) %>% t()

             [,1]       [,2]       [,3]        [,4]
 [1,] 98.45703803  0.5044549  0.7077342  0.33077286
 [2,]  0.43464717  0.8476126  0.7323841 97.98535613
 [3,]  0.49888670 98.6968386  0.7889767  0.01529801
 [4,]  0.18572028 98.8084679  0.7753605  0.23045127
 [5,]  0.26143714  0.6571831  0.8050750 98.27630478
 [6,]  0.99640796  0.7799081 97.6837717  0.53991230
 [7,] 98.78978531  0.4819841  0.1272817  0.60094890
 [8,]  0.78214576  0.9553001  0.2729379 97.98961630
 [9,] 98.13567866  0.9543617  0.5649977  0.34496192
[10,]  0.32951068 98.8431607  0.1326318  0.69469690
[11,]  0.13029270 99.0047771  0.3216674  0.54326273
[12,]  0.15043569  0.4000828 98.6757551  0.77372646
[13,]  0.45297697 98.5430059  0.7859616  0.21805559
[14,] 97.47082516  0.9589021  0.7300726  0.84020013
[15,] 97.50361108  0.5948120  0.9876713  0.91390557
[16,]  0.86724965 98.3732842  0.5026257  0.25684039
[17,]  0.75680131  0.8280581  0.4436990 97.97144160
[18,]  0.15198919  0.1043612 99.5793600  0.16428958
[19,] 98.65227018  0.4529603  0.4508067  0.44396285
[20,]  0.20336426  0.8484132 98.7985358  0.14968676
[21,]  0.25826836 99.0934157  0.6310231  0.01729282
[22,] 98.27614706  0.7532277  0.3868047  0.58382045
[23,]  0.86299051  0.9929164 97.5336993  0.61039375
[24,]  0.07155582  0.9499954  0.6848183 98.29363043
[25,]  0.36991300  0.7233306  0.3723177 98.53443872
[26,]  0.03545737  0.7313207  0.8334232 98.39979873
[27,]  0.38340609  0.4898682 98.3565145  0.77021122
[28,]  0.72959183  0.5986000  0.1162227 98.55558540
[29,] 97.61277655  0.8022139  0.7579463  0.82706325
[30,]  0.80788628  0.1048696 98.1646357  0.92260843

或者，如果可以接受，您可以简单地修改用于生成矩阵的当前代码 -

y <- t(replicate(30,{x <- runif(3); y <- c(x, 100 - sum(x)); sample(y/sum(y) * 100)}))

y
              [,1]        [,2]        [,3]        [,4]
 [1,] 3.388508e-01  0.11505273 99.07052567  0.47557081
 [2,] 9.782913e-01 97.67516922  0.93676869  0.40977080
 [3,] 7.118235e-01 98.57114227  0.61125057  0.10578368
 [4,] 4.114222e-01  0.71719168  0.57760052 98.29378560
 [5,] 9.933095e+01  0.02851812  0.48623365  0.15429983
 [6,] 1.178631e-01  0.52041776 98.87709291  0.48462625
 [7,] 2.934292e-01  0.65442844  0.54952687 98.50261552
 [8,] 9.894548e+01  0.37970274  0.51812253  0.15669579
 [9,] 9.866654e+01  0.57343925  0.58184710  0.17817812
[10,] 4.032940e-01 98.51693576  0.72129771  0.35847251
[11,] 9.781653e+01  0.61351868  0.74988068  0.82007274
[12,] 9.162155e-01  0.59539127  0.30124899 98.18714421
[13,] 6.278136e-01  0.02925863 98.46212355  0.88080426
[14,] 7.046555e-01  0.52923678  0.65325927 98.11284847
[15,] 3.208775e-01 98.31748802  0.61381891  0.74781558
[16,] 9.828647e+01  0.69667227  0.71976278  0.29709852
[17,] 3.696794e-04  0.69169085  0.13164316 99.17629630
[18,] 1.911561e-01  0.34213257 98.63355941  0.83315194
[19,] 1.784691e-01  0.11677341  0.35504916 99.34970828
[20,] 9.953998e-01  0.08634864  0.62682837 98.29142318
[21,] 8.658657e-01  0.20322069 98.67518541  0.25572820
[22,] 6.421388e-01 97.80948669  0.90228079  0.64609376
[23,] 9.843660e+01  0.84248163  0.05995064  0.66096543
[24,] 8.971966e-01  0.26555262  0.18558822 98.65166255
[25,] 2.468929e-01  0.09061412 99.09220658  0.57028645
[26,] 5.551374e-01  0.56177760 98.15917879  0.72390625
[27,] 9.812421e+01  0.62237186  0.52028315  0.73313957
[28,] 2.610207e-01 98.73290082  0.66234590  0.34373259
[29,] 5.671531e-01  0.34175286 99.05314043  0.03795362
[30,] 4.771366e-02  0.69462738 98.65743305  0.60022591