 
  Data Structure Data Structure
 Networking Networking
 RDBMS RDBMS
 Operating System Operating System
 Java Java
 MS Excel MS Excel
 iOS iOS
 HTML HTML
 CSS CSS
 Android Android
 Python Python
 C Programming C Programming
 C++ C++
 C# C#
 MongoDB MongoDB
 MySQL MySQL
 Javascript Javascript
 PHP PHP
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
How to 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
Advertisements
 