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How to find the mean of a square matrix elements by excluding diagonal elements in R?
There are many ways to find the mean of a matrix elements by excluding diagonal elements, this mean is actually the mean of lower triangular matrix and the upper triangular matrix. We can simply use mean function by creating a vector of lower and upper triangular matrix as shown in the below examples.
Example1
> M1<-matrix(rpois(20,5),nrow=5) > M1
Output
[,1] [,2] [,3] [,4] [1,] 1 6 3 6 [2,] 8 5 3 4 [3,] 5 4 4 6 [4,] 5 5 3 4 [5,] 4 8 1 3
Example
> mean(c(M1[upper.tri(M1)],M1[lower.tri(M1)]))
Output
[1] 4.625
Example2
> M2<-matrix(rpois(100,5),ncol=10) > M2
Output
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 3 7 2 4 10 9 4 7 3 2 [2,] 3 4 5 5 7 4 7 2 5 5 [3,] 3 2 3 12 5 2 3 4 6 4 [4,] 2 4 6 1 7 4 8 10 8 0 [5,] 6 4 4 4 7 4 7 4 5 7 [6,] 5 8 6 5 9 7 5 4 4 1 [7,] 5 3 5 3 6 1 1 9 6 1 [8,] 7 4 5 1 6 5 2 6 5 5 [9,] 4 7 6 8 4 4 7 5 1 6 [10,] 1 9 4 4 1 2 2 5 5 4
Example
> mean(c(M2[upper.tri(M2)],M2[lower.tri(M2)]))
Output
[1] 4.844444
Example3
> M3<-matrix(rnorm(36,6,2.1),nrow=6) > M3
Output
[,1] [,2] [,3] [,4] [,5] [,6] [1,] 11.102747 3.667257 2.674908 1.685490 7.297186 3.675492 [2,] 5.514661 7.012920 5.452867 5.890710 3.347643 4.944706 [3,] 5.842299 5.090597 5.764840 5.274849 7.210516 6.025230 [4,] 4.848784 6.171407 5.374152 10.452946 5.642747 8.886984 [5,] 9.387442 9.055521 8.677278 5.539050 5.648067 6.655354 [6,] 8.664883 5.976989 3.664106 5.527728 6.268774 8.135999
Example
> mean(c(M3[upper.tri(M3)],M3[lower.tri(M3)]))
Output
[1] 5.797854
Example4
> M4<-matrix(sample(11:20,64,replace=TRUE),nrow=8) > M4
Output
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 18 12 18 16 19 15 17 15 [2,] 11 11 20 18 13 19 13 15 [3,] 12 14 17 17 19 12 11 13 [4,] 18 14 14 19 16 19 11 11 [5,] 11 19 15 19 12 20 17 17 [6,] 18 19 15 12 14 15 20 19 [7,] 20 16 16 19 18 20 14 11 [8,] 12 20 13 19 20 19 11 16
Example
> mean(c(M4[upper.tri(M4)],M4[lower.tri(M4)]))
Output
[1] 15.91071
Example5
> M5<-matrix(runif(36,2,10),ncol=6) > M5
Output
[,1] [,2] [,3] [,4] [,5] [,6] [1,] 5.315719 7.590613 2.964828 2.510046 8.887437 3.377134 [2,] 3.393052 3.308531 5.938284 9.757756 7.803694 7.147399 [3,] 7.140688 7.942123 9.287733 6.907886 4.403413 2.938388 [4,] 3.171102 6.164160 4.408718 6.946996 5.626955 9.479825 [5,] 6.982951 8.210883 3.677973 9.643256 6.250810 6.695614 [6,] 7.575222 9.967751 6.816987 3.348135 7.717623 6.192853
Example
> mean(c(M5[upper.tri(M5)],M5[lower.tri(M5)]))
Output
[1] 6.272997
Example6
> M6<-matrix(sample(501:999,64),nrow=8) > M6
Output
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 990 725 549 896 867 619 764 682 [2,] 602 593 579 829 538 964 939 864 [3,] 889 878 851 911 886 834 693 730 [4,] 736 969 603 545 849 936 515 532 [5,] 982 856 771 925 877 972 647 570 [6,] 890 655 961 883 504 843 950 537 [7,] 766 726 628 870 899 585 687 536 [8,] 853 633 560 729 887 680 527 629
Example
> mean(c(M6[upper.tri(M6)],M6[lower.tri(M6)]))
Output
[1] 756.4286
Updated on: 23-Nov-2020
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