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法律研究如何在 R 中查找向量值之间的绝对成对差？
如果一个向量包含五个值，那么将会有十个成对差异。例如，假设我们有五个从 1 开始的数字，那么这些值的成对组合将是 (1,2)、(1,3)、(1,4)、(1,5)、(2,3)、(2,4)、(2,5)、(3,4)、(3,5)、(4,5)。现在要找到绝对成对差异，我们需要找到这些组合之间的差异，并取答案的绝对值，因此结果将是 1、2、3、4、1、2、3、1、2、1。
示例
x1<-1:3 abs(apply(combn(x1,2),2,diff))
输出
[1] 1 2 1
示例
x2<-1:10 abs(apply(combn(x2,2),2,diff))
输出
[1] 1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 1 2 3 4 5 6 1 2 3 4 5 1 2 3 [39] 4 1 2 3 1 2 1
示例
x3<-0:20 abs(apply(combn(x3,2),2,diff))
输出
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 1 2 3 4 5 [26] 6 7 8 9 10 11 12 13 14 15 16 17 18 19 1 2 3 4 5 6 7 8 9 10 11 [51] 12 13 14 15 16 17 18 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 1 [76] 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1 2 3 4 5 6 7 8 9 10 [101] 11 12 13 14 15 1 2 3 4 5 6 7 8 9 10 11 12 13 14 1 2 3 4 5 6 [126] 7 8 9 10 11 12 13 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 [151] 7 8 9 10 11 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 1 [176] 2 3 4 5 6 7 8 1 2 3 4 5 6 7 1 2 3 4 5 6 1 2 3 4 5 [201] 1 2 3 4 1 2 3 1 2 1
示例
x4<-rnorm(12,1,0.75) x4
输出
[1] 0.5973664 0.5388115 -0.2435155 0.5167396 1.3219034 0.9080164 [7] 0.4023727 0.9431512 1.5896491 0.5385002 0.4772925 1.7824402
abs(apply(combn(x4,2),2,diff))
[1] 0.93873134 0.21594628 0.65896714 0.76184515 1.21649873 0.28351827 [7] 0.42856328 2.15129690 0.25332961 1.01437721 0.37057314 0.72278506 [13] 0.27976420 0.17688619 0.27776739 0.65521307 0.51016805 1.21256557 [19] 0.68540173 1.95310854 1.30930447 0.44302086 0.54589887 1.00055245 [25] 0.06757199 0.21261700 1.93535062 0.03738333 1.23032349 0.58651942 [31] 0.10287801 0.55753159 0.37544887 0.23040386 1.49232976 0.40563753 [37] 1.67334435 1.02954027 0.45465358 0.47832688 0.33328186 1.38945176 [43] 0.50851554 1.77622235 1.13241828 0.93298046 0.78793545 0.93479817 [49] 0.96316912 2.23087594 1.58707187 0.14504502 1.86777864 0.03018866 [55] 1.29789547 0.65409140 1.72273362 0.17523367 1.44294049 0.79913642 [61] 1.89796729 3.16567411 2.52187004 1.26770682 0.62390274 0.64380407
示例
x5<-rpois(20,5) x5
输出
[1] 4 4 5 9 4 5 4 5 4 6 4 1 2 3 4 4 5 4 5 6
abs(apply(combn(x5,2),2,diff))
[1] 3 2 0 5 2 3 2 0 6 0 3 1 5 3 1 2 4 2 8 1 3 2 1 0 1 3 3 3 0 4 2 0 2 1 1 1 5 [38] 2 3 0 1 0 2 4 2 1 3 3 1 1 0 2 0 6 5 2 3 2 0 6 0 3 1 5 3 1 2 4 2 8 3 2 3 5 [75] 1 5 2 6 0 2 4 3 1 3 3 1 0 2 4 2 1 3 3 1 1 0 2 0 6 1 3 3 3 0 4 2 0 2 1 1 1 [112] 5 2 4 2 1 3 3 1 1 0 2 0 6 6 0 3 1 5 3 1 2 4 2 8 6 3 7 1 3 5 4 2 4 2 3 1 5 [149] 3 1 2 4 2 8 4 2 0 2 1 1 1 5 6 4 2 3 5 3 9 2 4 3 1 3 3 2 1 1 1 5 1 3 1 7 2 [186] 0 6 2 4 6
示例
x6<-rexp(12,5) x6
输出
[1] 0.214630942 0.791414235 0.141469153 0.047114274 0.047027378 0.333190073 [7] 0.002508767 0.016951547 0.124172744 0.163973518 0.260396594 0.010264201
abs(apply(combn(x6,2),2,diff))
[1] 0.306139776 0.329170981 0.275865536 0.002470828 0.016591242 0.966078530 [7] 0.176470691 0.196067564 0.041360872 0.027528765 0.084748488 0.023031206 [13] 0.030274239 0.303668948 0.289548533 0.659938754 0.129669085 0.110072212 [19] 0.264778903 0.278611011 0.221391287 0.053305445 0.326700154 0.312579739 [25] 0.636907549 0.152700290 0.133103417 0.287810109 0.301642216 0.244422493 [31] 0.273394709 0.259274294 0.690212994 0.099394846 0.079797972 0.234504664 [37] 0.248336771 0.191117048 0.014120414 0.963607702 0.173999863 0.193596736 [43] 0.038890045 0.025057937 0.082277661 0.949487288 0.159879449 0.179476322 [49] 0.024769630 0.010937523 0.068157246 0.789607839 0.770010966 0.924717658 [55] 0.938549765 0.881330042 0.019596873 0.135109818 0.148941926 0.091722202 [61] 0.154706692 0.168538799 0.111319076 0.013832108 0.043387616 0.057219723
示例
x7<-round(runif(20,3,5),0) x7
输出
[1] 5 4 4 4 4 5 3 4 5 5 3 4 5 4 4 4 5 4 5 4
abs(apply(combn(x7,2),2,diff))
[1] 1 1 1 1 0 2 1 0 0 2 1 0 1 1 1 0 1 0 1 0 0 0 1 1 0 1 1 1 0 1 0 0 0 1 0 1 0 [38] 0 0 1 1 0 1 1 1 0 1 0 0 0 1 0 1 0 0 1 1 0 1 1 1 0 1 0 0 0 1 0 1 0 1 1 0 1 [75] 1 1 0 1 0 0 0 1 0 1 0 2 1 0 0 2 1 0 1 1 1 0 1 0 1 1 2 2 0 1 2 1 1 1 2 1 2 [112] 1 1 1 1 0 1 0 0 0 1 0 1 0 0 2 1 0 1 1 1 0 1 0 1 2 1 0 1 1 1 0 1 0 1 1 2 1 [149] 1 1 2 1 2 1 1 0 0 0 1 0 1 0 1 1 1 0 1 0 1 0 0 1 0 1 0 0 1 0 1 0 1 0 1 0 1 [186] 0 1 1 0 1
示例
x8<-sample(0:9,20,replace=TRUE) x8
输出
[1] 0 3 5 9 1 3 4 6 5 6 4 5 8 5 2 6 9 9 3 4
abs(apply(combn(x8,2),2,diff))
[1] 3 5 9 1 3 4 6 5 6 4 5 8 5 2 6 9 9 3 4 2 6 2 0 1 3 2 3 1 2 5 2 1 3 6 6 0 1 [38] 4 4 2 1 1 0 1 1 0 3 0 3 1 4 4 2 1 8 6 5 3 4 3 5 4 1 4 7 3 0 0 6 5 2 3 5 4 [75] 5 3 4 7 4 1 5 8 8 2 3 1 3 2 3 1 2 5 2 1 3 6 6 0 1 2 1 2 0 1 4 1 2 2 5 5 1 [112] 0 1 0 2 1 2 1 4 0 3 3 3 2 1 1 0 3 0 3 1 4 4 2 1 2 1 2 1 4 0 3 3 3 2 1 4 1 [149] 2 2 5 5 1 0 3 0 3 1 4 4 2 1 3 6 2 1 1 5 4 3 1 4 4 2 1 4 7 7 1 2 3 3 3 2 0 [186] 6 5 6 5 1
示例
x9<-sample(rnorm(10),12,replace=TRUE) x9
输出
[1] 0.43737176 -2.22651843 2.36890565 -0.49296800 -2.22651843 -0.88688207 [7] 2.36890565 -0.41582556 0.74190591 -2.22651843 -0.88688207 0.03418781
abs(apply(combn(x9,2),2,diff))
[1] 0.436617762 1.437561238 1.254929774 1.979603739 0.670434157 1.257986597 [7] 0.670434157 0.621070420 1.855088939 1.254929774 1.979603739 1.000943476 [13] 0.818312012 1.542985977 0.233816396 0.821368836 0.233816396 0.184452658 [19] 1.418471177 0.818312012 1.542985977 0.182631464 0.542042501 0.767127081 [25] 0.179574641 0.767127081 0.816490818 0.417527701 0.182631464 0.542042501 [31] 0.724673965 0.584495617 0.003056823 0.584495617 0.633859354 0.600159165 [37] 0.000000000 0.724673965 1.309169581 0.721617141 1.309169581 1.358533319 [43] 0.124514800 0.724673965 0.000000000 0.587552440 0.000000000 0.049363737 [49] 1.184654782 0.584495617 1.309169581 0.587552440 0.636916178 0.597102342 [55] 0.003056823 0.721617141 0.049363737 1.184654782 0.584495617 1.309169581 [61] 1.234018519 0.633859354 1.358533319 0.600159165 0.124514800 0.724673965
示例
x10<-sample(rpois(10,2),12,replace=TRUE) x10
输出
[1] 5 1 2 2 4 0 1 5 5 2 2 1
abs(apply(combn(x10,2),2,diff))
[1] 3 0 3 0 3 3 4 0 4 0 4 3 0 3 0 0 1 3 1 3 1 3 0 3 3 4 0 4 0 4 3 0 0 1 3 1 3 1 [39] 3 3 4 0 4 0 4 0 1 3 1 3 1 1 3 1 3 1 4 0 4 0 4 0 4 4 0 4
更新于：2020年10月8日
384 次浏览
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