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How to find the variance of row elements of a matrix in R?
Finding the variance of columns is a common task in data analysis but often data is provided in wide format instead of long format, therefore, the cases are represented vertically and the variables are aligned horizontally and this data could be available in matrix or any other form. Therefore, the variance can be easily found by using apply function.
Example
M1<-matrix(1:25,ncol=5) M1
Output
[,1] [,2] [,3] [,4] [,5] [1,] 1 6 11 16 21 [2,] 2 7 12 17 22 [3,] 3 8 13 18 23 [4,] 4 9 14 19 24 [5,] 5 10 15 20 25
Example
apply(M1,1,var)
Output
[1] 62.5 62.5 62.5 62.5 62.5
Example
M2<-matrix(1:100,nrow=10) M2
Output
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 1 11 21 31 41 51 61 71 81 91 [2,] 2 12 22 32 42 52 62 72 82 92 [3,] 3 13 23 33 43 53 63 73 83 93 [4,] 4 14 24 34 44 54 64 74 84 94 [5,] 5 15 25 35 45 55 65 75 85 95 [6,] 6 16 26 36 46 56 66 76 86 96 [7,] 7 17 27 37 47 57 67 77 87 97 [8,] 8 18 28 38 48 58 68 78 88 98 [9,] 9 19 29 39 49 59 69 79 89 99 [10,] 10 20 30 40 50 60 70 80 90 100
Example
apply(M2,1,var)
Output
[1] 916.6667 916.6667 916.6667 916.6667 916.6667 916.6667 916.6667 916.6667 [9] 916.6667 916.6667
Example
M3<-matrix(1:60,nrow=20) M3
Output
[,1] [,2] [,3] [1,] 1 21 41 [2,] 2 22 42 [3,] 3 23 43 [4,] 4 24 44 [5,] 5 25 45 [6,] 6 26 46 [7,] 7 27 47 [8,] 8 28 48 [9,] 9 29 49 [10,] 10 30 50 [11,] 11 31 51 [12,] 12 32 52 [13,] 13 33 53 [14,] 14 34 54 [15,] 15 35 55 [16,] 16 36 56 [17,] 17 37 57 [18,] 18 38 58 [19,] 19 39 59 [20,] 20 40 60
Example
apply(M3,1,var)
Output
[1] 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 [20] 400
Example
M4<-matrix(rnorm(30,5,1),nrow=15) M4
Output
[,1] [,2] [1,] 5.517894 6.105346 [2,] 4.008269 3.640526 [3,] 5.484878 6.779180 [4,] 4.534817 6.723722 [5,] 5.602067 4.032113 [6,] 5.884524 4.910336 [7,] 3.234350 5.824891 [8,] 4.188615 4.874050 [9,] 3.367234 5.062664 [10,] 6.430093 3.369706 [11,] 4.364802 5.902848 [12,] 5.536012 7.037217 [13,] 5.096840 4.269251 [14,] 6.154817 4.320163 [15,] 5.070610 5.150351
Example
apply(M4,1,var)
Output
[1] 0.021906088 0.711543659 0.632177226 0.822552459 0.273495182 1.132347512 [7] 0.058730197 1.369282431 1.130733174 0.625609262 2.226411932 0.081628957 [13] 0.237108400 0.001073659 0.011819879
Example
M5<-matrix(runif(40,1,2),nrow=20) M5
Output
[,1] [,2] [1,] 1.797724 1.045920 [2,] 1.663738 1.404009 [3,] 1.751550 1.920017 [4,] 1.250277 1.445597 [5,] 1.344217 1.975511 [6,] 1.186875 1.877203 [7,] 1.232352 1.912921 [8,] 1.848107 1.016703 [9,] 1.997422 1.888561 [10,] 1.370770 1.548419 [11,] 1.564406 1.925559 [12,] 1.316188 1.024001 [13,] 1.373600 1.642644 [14,] 1.880770 1.861855 [15,] 1.230204 1.628706 [16,] 1.339799 1.782240 [17,] 1.128182 1.186216 [18,] 1.862291 1.140511 [19,] 1.541293 1.454260 [20,] 1.332327 1.398676
Example
apply(M5,1,var)
Output
[1] 3.995889e-05 2.476911e-01 9.689490e-02 3.826634e-02 6.342112e-06 [6] 2.507245e-02 2.410225e-01 7.566494e-02 2.419975e-02 2.205656e-02 [11] 3.307264e-03 1.020207e-01 2.852077e-01 1.436173e-01 4.729889e-03 [16] 4.647355e-02 1.425541e-01 4.943002e-03 4.128207e-02 7.227659e-03
Updated on: 16-Oct-2020
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