library(pracma)
library(MASS)
\[\mathbf{A} = \left[\begin{array} {rrr} 1 & 2 & 3 & 4 \\ -1 & 0 & 1 & 3 \\ 0 & 1 & -2 & 1 \\ 5 & 4 & -2 & -3 \end{array}\right] \]
A <- matrix(c(1,2,3,4,-1,0,1,3,0,1,-2,1,5,4,-2,-3),nrow=4)
A
## [,1] [,2] [,3] [,4]
## [1,] 1 -1 0 5
## [2,] 2 0 1 4
## [3,] 3 1 -2 -2
## [4,] 4 3 1 -3
Reduce to echelon form and find the rank
rref(A)
## [,1] [,2] [,3] [,4]
## [1,] 1 0 0 0
## [2,] 0 1 0 0
## [3,] 0 0 1 0
## [4,] 0 0 0 1
Rank(A)
## [1] 4
The Rank of A is 4
\[\mathbf{B} = \left[\begin{array} {rrr} 1 & 2 & 1 \\ 3 & 6 & 3 \\ 2 & 4 & 2 \end{array}\right] \]
By looking at matrix B we can easily determine that it has a rank of 1 because row 2 and 3 are scalar multiples of row 1. Thus, they are linearly dependent.
Get the rank using the Rank function we will get the same result
B <- matrix(c(1,2,1,3,6,3,2,4,2),nrow=3)
B
## [,1] [,2] [,3]
## [1,] 1 3 2
## [2,] 2 6 4
## [3,] 1 3 2
Reduce to echelon form and find the rank
rref(B)
## [,1] [,2] [,3]
## [1,] 1 3 2
## [2,] 0 0 0
## [3,] 0 0 0
Rank(B)
## [1] 1
\[\mathbf{A} = \left[\begin{array} {rrr} 1 & 2 & 3 \\ 0 & 4 & 5 \\ 0 & 0 & 6 \end{array}\right] \]
Solution
Find the eigenvalue of A using the rule of sarrus:
\[\mathbf{p(\lambda)} = \left[\begin{array} {rrr} \lambda -1 & -2 & -3 & \lambda -1 & -2 \\ 0 & \lambda -4 & -5 & 0 & \lambda -4 \\ 0 & 0 & \lambda -6 & 0 & 0 \end{array}\right] \]
\[ p(\lambda) = (\lambda -1)(\lambda-4)(\lambda-6)+0+0-0-0-0 \]
\[ (\lambda -1)= 0 => \lambda = 1\] \[ (\lambda -4)= 0 => \lambda = 4\] \[ (\lambda -6)= 0 => \lambda = 6\]
We can also use the eigen function to find the eigen values of A matrix
A <- matrix(c(1,2,3,0,4,5,0,0,6),nrow=3, byrow=T)
A
## [,1] [,2] [,3]
## [1,] 1 2 3
## [2,] 0 4 5
## [3,] 0 0 6
Lambda<-eigen(A)$value
Lambda
## [1] 6 4 1
Find the eigenvectors of A:
L=1
L1 <- matrix(c(L-1,-2,-3,0,L-4,-5,0,0,L-6),nrow=3, byrow=T)
L1
## [,1] [,2] [,3]
## [1,] 0 -2 -3
## [2,] 0 -3 -5
## [3,] 0 0 -5
Reduce to echelon form
rref(L1)
## [,1] [,2] [,3]
## [1,] 0 1 0
## [2,] 0 0 1
## [3,] 0 0 0
\(( \lambda I_3 - A )v = \left[ {\begin{array}{ccc} 0 & 1 & 0\\ 0 & 0 & 1\\ 0 & 0 & 0\ \end{array} } \right] \left[ {\begin{array}{c} v_1\\ v_2\\ v_3\ \end{array} } \right]\)
\(v_2 = 0 \\ v_3 = 0 \\ v_1 = 1\)
Let \(v_1 = a\)
\(E_{\lambda = 1} = a \left[ {\begin{array}{c} 1\\ 0\\ 0\ \end{array} } \right]\)
L=4
L4 <- matrix(c(L-1,-2,-3,0,L-4,-5,0,0,L-6),nrow=3, byrow=T)
L4
## [,1] [,2] [,3]
## [1,] 3 -2 -3
## [2,] 0 0 -5
## [3,] 0 0 -2
Reduce to echelon form
r=rref(L4)
fractions(r)
## [,1] [,2] [,3]
## [1,] 1 -2/3 0
## [2,] 0 0 1
## [3,] 0 0 0
\(( \lambda I_3 - A )v = \left[ {\begin{array}{ccc} 1 &-2/3 & 0\\ 0 & 0 & 1\\ 0 & 0 & 0\ \end{array} } \right] \left[ {\begin{array}{c} v_1\\ v_2\\ v_3\ \end{array} } \right]\)
\(v_2 = 2/3 v_2 \\ v_3 = 0 \\ v2 = 1\)
Let \(v_2 = b\)
\(E_{\lambda = 4} = b \left[ {\begin{array}{c} 2/3\\ 1\\ 0\ \end{array} } \right]\)
L=6
L6 <- matrix(c(L-1,-2,-3,0,L-4,-5,0,0,L-6),nrow=3,byrow=T)
L6
## [,1] [,2] [,3]
## [1,] 5 -2 -3
## [2,] 0 2 -5
## [3,] 0 0 0
Reduce to echelon form
r=rref(L6)
fractions(r)
## [,1] [,2] [,3]
## [1,] 1 0 -8/5
## [2,] 0 1 -5/2
## [3,] 0 0 0
\(( \lambda I_3 - A )v = \left[ {\begin{array}{ccc} 1 & 0 & -8/5\\ 0 & 1 & -5/2\\ 0 & 0 & 0\ \end{array} } \right] \left[ {\begin{array}{c} v_1\\ v_2\\ v_3\ \end{array} } \right]\)
\(v_1 = 8/5 v_3 \\ v_2 = 5/2 v_3 , v3=1\)
Let \(v_3 = c\)
\(E_{\lambda = 6} = c \left[ {\begin{array}{c} 8/5\\ 5/2\\ 1\ \end{array} } \right]\)