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Convert Diagonal Elements of a Matrix in R into Missing Values
First thing we need to understand is diagonal elements are useful only if we have a square matrix, otherwise it would not make sense to set diagonal elements, this is known to almost all mathematicians but some freshman might get confused because we can create diagonal in a non-square matrix which should not be called a diagonal. In R, we can set the diagonal elements of a matrix to missing values/NA by using diag function.
Example1
> M1<-matrix(1:16,nrow=4) > M1
Output
[,1] [,2] [,3] [,4] [1,] 1 5 9 13 [2,] 2 6 10 14 [3,] 3 7 11 15 [4,] 4 8 12 16
Example
> diag(M1)<-NA > M1
Output
[,1] [,2] [,3] [,4] [1,] NA 5 9 13 [2,] 2 NA 10 14 [3,] 3 7 NA 15 [4,] 4 8 12 NA
Example2
> M2<-matrix(rpois(100,10),nrow=10) > M2
Output
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 13 18 9 5 15 7 14 7 9 14 [2,] 11 10 12 6 11 13 11 12 6 11 [3,] 12 13 6 6 11 18 9 12 9 6 [4,] 13 14 11 17 17 6 5 10 8 11 [5,] 10 9 15 11 10 14 6 5 5 15 [6,] 8 15 6 10 8 8 10 7 11 7 [7,] 10 12 8 9 12 15 19 9 10 15 [8,] 15 9 4 13 4 13 10 9 11 11 [9,] 7 6 11 12 3 8 12 8 8 11 [10,] 12 13 13 9 11 11 6 6 7 10
Example
> diag(M2)<-NA > M2
Output
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] NA 18 9 5 15 7 14 7 9 14 [2,] 11 NA 12 6 11 13 11 12 6 11 [3,] 12 13 NA 6 11 18 9 12 9 6 [4,] 13 14 11 NA 17 6 5 10 8 11 [5,] 10 9 15 11 NA 14 6 5 5 15 [6,] 8 15 6 10 8 NA 10 7 11 7 [7,] 10 12 8 9 12 15 NA 9 10 15 [8,] 15 9 4 13 4 13 10 NA 11 11 [9,] 7 6 11 12 3 8 12 8 NA 11 [10,] 12 13 13 9 11 11 6 6 7 NA
Example3
> M3<-matrix(rpois(25,3),nrow=5) > M3
Output
[,1] [,2] [,3] [,4] [,5] [1,] 2 3 4 2 4 [2,] 2 2 3 5 3 [3,] 3 7 6 1 5 [4,] 1 1 4 1 4 [5,] 1 2 0 1 5
Example
> diag(M3)<-NA > M3
Output
[,1] [,2] [,3] [,4] [,5] [1,] NA 3 4 2 4 [2,] 2 NA 3 5 3 [3,] 3 7 NA 1 5 [4,] 1 1 4 NA 4 [5,] 1 2 0 1 NA
Example4
> M4<-matrix(rnorm(36,5,2.5),nrow=6) > M4
Output
[,1] [,2] [,3] [,4] [,5] [,6] [1,] 7.449650 2.977026 3.631003 1.588073 6.4641515 4.9833353 [2,] 4.326318 4.327728 6.790520 2.367960 0.9577471 5.4084005 [3,] 3.143312 6.766010 5.364526 2.544719 7.9256179 -0.8116725 [4,] 5.983452 5.340530 2.530320 6.830628 4.0030207 7.1645111 [5,] 4.073458 1.795408 -2.391053 6.320859 4.5389839 1.0296674 [6,] 3.739790 6.036844 6.171213 6.901320 5.5595449 4.9644731
Example
> diag(M4)<-NA > M4
Output
[,1] [,2] [,3] [,4] [,5] [,6] [1,] NA 2.977026 3.631003 1.588073 6.4641515 4.9833353 [2,] 4.326318 NA 6.790520 2.367960 0.9577471 5.4084005 [3,] 3.143312 6.766010 NA 2.544719 7.9256179 -0.8116725 [4,] 5.983452 5.340530 2.530320 NA 4.0030207 7.1645111 [5,] 4.073458 1.795408 -2.391053 6.320859 NA 1.0296674 [6,] 3.739790 6.036844 6.171213 6.901320 5.5595449 NA
Example5
> M5<-matrix(runif(25,2,5),nrow=5) > M5
Output
[,1] [,2] [,3] [,4] [,5] [1,] 2.753600 3.017767 2.923270 2.532730 3.425423 [2,] 2.742611 2.398763 4.906797 4.273442 3.416288 [3,] 2.744358 4.227648 3.690739 3.508798 3.423980 [4,] 3.124375 2.363392 3.336010 4.770364 3.294046 [5,] 3.468065 3.424600 2.667044 2.623021 4.055215
Example
> diag(M5)<-NA > M5
Output
[,1] [,2] [,3] [,4] [,5] [1,] NA 3.017767 2.923270 2.532730 3.425423 [2,] 2.742611 NA 4.906797 4.273442 3.416288 [3,] 2.744358 4.227648 NA 3.508798 3.423980 [4,] 3.124375 2.363392 3.336010 NA 3.294046 [5,] 3.468065 3.424600 2.667044 2.623021 NA
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