A = matrix(c(1,-1,0,5,2,0,1,4,3,1,-2,-2,4,3,1,-3),4,4)
A
## [,1] [,2] [,3] [,4]
## [1,] 1 2 3 4
## [2,] -1 0 1 3
## [3,] 0 1 -2 1
## [4,] 5 4 -2 -3
qr(A)$rank
## [1] 4
Since each row is linear independent from other rows, the rank of the matrix is 4.
The maximum rank can be equal or less than n, the minimum rank of non-zero matrix is 1.
B = matrix(c(1, 3, 2, 2, 6, 4, 1, 3, 2),3,3)
B
## [,1] [,2] [,3]
## [1,] 1 2 1
## [2,] 3 6 3
## [3,] 2 4 2
qr(B)$rank
## [1] 1
2* B[1,] == B[3,]
## [1] TRUE TRUE TRUE
3* B[1,] == B[2,]
## [1] TRUE TRUE TRUE
Since each row is not linearly independent with other rows, the rank of B is 1.
\[\mathbf{A} = \left[\begin{array} {rrr} 1 & 2 & 3 \\ 0 & 4 & 5 \\ 0 & 0 & 6 \end{array}\right] \]
\[ \lambda E-A= \left[\begin{array} {rrr} \lambda - 1 & -2 & -3 \\ 0 & \lambda -4 & -5 \\ 0 & 0 & \lambda -6 \end{array}\right] \\ det(\lambda E-A) = (\lambda -1 )(\lambda - 4)(\lambda -6 ) = 0 \\ \lambda^{3}-11\lambda^{2}+34\lambda - 24 = 0 \\ Eigenvalue: \lambda_1 = 6 , \lambda_2 = 4, \lambda_3 = 1 \\ \] Now we need to use the eigenvalue to calculate the eigenvectors:
\[ (\lambda_1 I-A)h_1 = 0 \\ \left[\begin{array} {rrr} 5 & -2 & -3 \\ 0 & 2 & -5 \\ 0 & 0 & 0 \end{array}\right]h_1 = \left[\begin{array} {rrr} 0 \\ 0 \\ 0\end{array}\right] \\ h_1 = \left[\begin{array} {rrr} 1.6 \\ 2.5 \\ 1\end{array}\right] \\ \] \[ (\lambda_2 I-A)h_2 = 0 \\ \left[\begin{array} {rrr} 3 & -2 & -3 \\ 0 & 0 & -5 \\ 0 & 0 & -2 \end{array}\right]h_2 = \left[\begin{array} {rrr} 0 \\ 0 \\ 0\end{array}\right] \\ h_2 = \left[\begin{array} {rrr} 1 \\ 1.5 \\ 0 \end{array}\right] \\ \]
\[ (\lambda_3 I-A)h_3 = 0 \\ \left[\begin{array} {rrr} 1 & -2 & -3 \\ 0 & -3 & -5 \\ 0 & 0 & -5 \end{array}\right]h_2 = \left[\begin{array} {rrr} 0 \\ 0 \\ 0\end{array}\right] \\ h_3 = \left[\begin{array} {rrr} 1 \\ 0 \\ 0 \end{array}\right] \\ \]