R中的范围函数提供最小值和最大值，而不是两者之间的差。因此，我们可以使用范围函数找到最小值和最大值，然后可以使用diff函数来找到实际范围。例如，如果我们有一个向量x，则可以使用diff（range(x)）找到范围。
> x1<-rpois(10,2) > x1
输出结果
[1] 4 2 3 0 2 3 1 3 4 2
> diff(range(x1))
输出结果
[1] 4
> x2<-rpois(150,5) > x2
输出结果
[1] 4 5 3 10 2 4 2 4 8 7 3 1 5 6 7 3 7 3 4 5 3 7 2 7 5 [26] 6 5 5 5 4 3 5 9 6 9 9 2 9 7 6 6 4 4 3 9 4 8 4 5 5 [51] 9 7 2 8 6 6 2 4 6 2 9 3 2 8 3 5 4 4 4 8 3 6 1 2 4 [76] 6 8 4 3 7 5 3 5 6 3 4 7 6 5 7 9 10 5 8 5 2 9 2 6 4 [101] 5 8 2 2 2 5 3 5 6 6 4 8 6 11 3 4 7 1 8 8 4 1 10 5 6 [126] 5 9 8 4 5 2 4 6 7 4 5 8 5 4 5 3 2 6 5 4 4 2 7 5 3
> diff(range(x2))
输出结果
[1] 10
> x3<-rpois(150,30) > x3
输出结果
[1] 25 33 25 27 16 36 28 34 38 26 37 42 24 27 26 24 30 45 30 27 27 37 29 28 26 [26] 32 24 25 33 38 41 37 29 24 35 28 36 23 22 22 31 38 24 26 26 27 45 24 30 36 [51] 29 27 16 27 30 28 35 43 34 40 29 24 21 25 32 24 33 30 32 34 34 29 19 30 25 [76] 24 31 25 26 32 26 29 32 29 28 30 27 29 25 29 28 28 31 26 28 28 20 24 34 44 [101] 25 26 39 28 23 32 33 28 31 39 28 24 28 20 36 31 38 32 27 29 43 38 37 27 28 [126] 25 32 25 36 34 35 24 33 24 22 24 21 32 23 29 38 23 25 20 31 43 27 29 35 25
> diff(range(x3))
输出结果
[1] 29
> x4<-sample(0:9,150,replace=TRUE) > x4
输出结果
[1] 6 0 8 1 6 7 0 7 4 5 3 4 3 4 7 5 3 1 5 8 0 8 3 8 0 5 8 3 7 5 2 8 5 1 5 6 1 [38] 3 7 9 2 4 6 2 2 7 8 4 4 3 3 4 8 4 7 0 2 9 1 5 5 0 8 6 3 1 8 4 6 6 2 7 7 5 [75] 3 4 1 1 3 6 2 5 0 4 2 6 9 7 1 4 7 8 0 0 7 4 3 6 7 8 9 1 9 1 0 1 7 5 9 6 5 [112] 8 2 3 7 1 7 2 1 3 3 3 9 9 8 6 4 3 0 9 3 7 2 1 6 8 7 8 6 3 8 8 5 2 9 3 4 2 [149] 4 8
> diff(range(x4))
输出结果
[1] 9
> x5<-sample(501:600,120,replace=TRUE) > x5
输出结果
[1] 540 565 570 516 554 567 537 529 506 538 505 598 541 509 585 576 557 544 [19] 545 584 555 552 569 552 559 510 588 505 522 589 534 588 583 507 574 529 [37] 587 593 578 592 536 584 575 545 572 569 542 513 531 558 548 503 565 550 [55] 554 569 512 592 548 590 555 560 583 512 531 530 597 544 578 597 527 598 [73] 543 573 530 597 542 576 532 583 591 585 578 592 600 553 573 511 506 574 [91] 600 583 526 553 584 569 561 523 550 503 584 531 584 590 548 597 514 512 [109] 546 518 591 563 542 559 509 557 579 590 563 538
> diff(range(x5))
输出结果
[1] 97
> x6<-sample(1000:9999,100) > x6
输出结果
[1] 8830 1194 8928 6862 8048 9203 8094 8305 4013 8804 2148 1538 9715 9509 8167 [16] 2043 4125 3493 2995 9546 4397 7277 1828 4994 4912 2761 1443 6171 2311 7058 [31] 7210 7909 4190 1726 6829 8934 2767 8300 6578 6029 1821 2752 9243 7321 5489 [46] 8126 4740 8921 2596 7429 8272 2314 4505 6407 9296 8975 8995 3809 1865 4282 [61] 2636 7475 3037 5119 7013 4030 2871 5044 8971 7672 8409 1126 4515 6966 2925 [76] 4434 7380 4924 2922 1110 9281 7212 2992 7138 3398 1078 1024 7004 5909 2719 [91] 2427 3951 2274 8114 1211 5491 1856 5252 8955 4633
> diff(range(x6))
输出结果
[1] 8691
> x7<-rnorm(60,1,0.95) > x7
输出结果
[1] 0.77732585 0.20340071 0.81968478 0.96607462 -1.20625378 1.13518917 [7] 1.49899894 0.54251191 0.72349942 1.31520105 -0.55316276 1.43105091 [13] 2.51926637 0.93088965 1.47562589 1.71550853 1.44065223 0.16561474 [19] -1.11521230 -0.75516868 1.51849795 1.45891592 2.09555983 -0.31360865 [25] 0.62348582 0.13172177 -0.05222773 0.83865212 0.93192698 1.29893029 [31] 2.96131722 2.02531440 2.00390166 1.17336233 2.22268897 -0.02296672 [37] 0.73884700 -0.65950707 1.55010346 1.56882173 1.87951054 0.72003358 [43] 0.68283502 0.58438396 -0.65058594 1.63307556 1.37260207 1.42002910 [49] 1.99269798 0.75585593 0.59646514 1.15462732 2.23040244 2.39621165 [55] -0.02079837 2.58771378 1.75922960 1.42400723 0.13761317 0.59743434
> diff(range(x7))
输出结果
[1] 4.167571
> x8<-rnorm(60,50,1.25) > x8
输出结果
[1] 50.60171 47.35250 48.96147 49.62938 51.50854 50.61273 48.56096 50.97370 [9] 49.15675 48.92862 49.11240 50.99810 49.65265 50.65235 50.44551 49.28134 [17] 47.91846 50.89146 50.70412 50.04375 50.14076 48.45254 50.91452 50.35164 [25] 49.02045 49.70859 49.49023 50.81482 48.77840 48.94855 49.35256 49.94870 [33] 50.49340 50.16679 48.81921 49.94986 50.89710 50.78883 51.04020 51.74803 [41] 50.01834 50.79934 49.62719 49.23445 50.65635 49.59964 49.37007 50.52736 [49] 49.58866 51.01773 49.40808 49.47980 50.17246 48.21275 49.11339 51.04322 [57] 48.92094 50.60240 50.45600 49.84697
> diff(range(x8))
输出结果
[1] 4.395527
> x9<-runif(50,2,5) > x9
输出结果
[1] 4.125960 2.396517 4.609997 2.473424 3.658801 2.407685 3.174801 4.383593 [9] 3.688843 2.125594 2.500938 4.126458 4.519009 4.411336 2.202806 2.290341 [17] 4.290165 4.287591 4.409094 3.121584 2.404941 4.626608 4.926589 4.700230 [25] 2.782749 2.844678 4.515919 3.670294 4.751767 4.942986 2.547970 3.278626 [33] 3.364280 4.102291 4.571044 3.554319 4.637315 4.143440 3.333218 3.997436 [41] 4.655782 3.663140 4.337505 4.517204 4.885042 3.040531 4.612726 2.489695 [49] 3.180844 3.445043
> diff(range(x9))
输出结果
[1] 2.817393
> x10<-rexp(50,3.12) > x10
输出结果
[1] 0.361924533 0.363733351 0.188424290 0.227219438 0.131665583 0.142529389 [7] 0.557993442 0.431907105 0.532919218 0.281745467 0.140911293 0.079761168 [13] 0.303477710 0.289148983 0.615317513 0.005794841 0.435995172 0.818063367 [19] 0.412843319 1.323551486 0.911916495 0.422450781 0.476757946 0.214319709 [25] 0.081348798 0.142734230 0.016998688 0.201221571 0.067065224 0.075520322 [31] 0.850355486 0.044162291 0.090631643 0.045846146 0.448331579 0.049561155 [37] 0.231546764 0.342187336 0.223755116 0.258201262 0.293556476 0.689359642 [43] 0.120444026 0.649185021 0.146372525 0.010746677 0.094800106 0.602121528 [49] 0.028487216 0.007054710
> diff(range(x10))
输出结果
[1] 1.317757