What is the rank of matrix A?
Solution:
\(A=\left[ \begin{array}{cccccc} 1 & 2 & 3 & 4 \\ -1 & 0 & 1 & 3 \\ 0 & 1 & -2 & 1 \\ 5 & 4 & -2 & -3 \end{array} \right]\rightarrow\) \(R2+R1, R4-5*R1\)
\(=\left[ \begin{array}{cccccc} 1 & 2 & 3 & 4 \\ 0 & 2 & 4 & 7 \\ 0 & 1 & -2 & 1 \\ 0 & -6 & -17 & -23 \end{array} \right]\rightarrow\) \(R2*0.5\)
\(=\left[ \begin{array}{cccccc} 1 & 2 & 3 & 4 \\ 0 & 1 & 2 & 3.5 \\ 0 & 1 & -2 & 1 \\ 0 & -6 & -17 & -23 \end{array} \right]\rightarrow R3-R2\) \(R4+6*R2\)
\(=\left[ \begin{array}{cccccc} 1 & 2 & 3 & 4 \\ 0 & 1 & 2 & 3.5 \\ 0 & 0 & 4 & -2.5 \\ 0 & 0 & -5 & -2 \end{array} \right]\rightarrow R3*0.25\)
\(=\left[ \begin{array}{cccccc} 1 & 2 & 3 & 4 \\ 0 & 1 & 2 & 3.5 \\ 0 & 0 & 1 & -0.625 \\ 0 & 0 & -5 & -2 \end{array} \right]\rightarrow R4+5*R3\)
\(=\left[ \begin{array}{cccccc} 1 & 2 & 3 & 4 \\ 0 & 1 & 2 & 3.5 \\ 0 & 0 & 1 & -0.625 \\ 0 & 0 & 0 & -6.125 \end{array} \right]\)
Answer: Rank is 4.
Checking in R.
a <- matrix(c(1,-1,0,5,2,0,1,4,3,1,-2,-2,4,3,1,-3), ncol = 4, nrow = 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
#install.packages("Matrix")
library(Matrix)
rankMatrix(a)
## [1] 4
## attr(,"method")
## [1] "tolNorm2"
## attr(,"useGrad")
## [1] FALSE
## attr(,"tol")
## [1] 8.881784e-16
Maximum rank is the minimum of m and n. In our case, it will be n. The minimum rank will be 1(all columns are lineary dependent) .
What is the rank of matrix B?
Solution:
\(B=\left[ \begin{array}{cccccc} 1 & 2 & 1 \\ 3 & 6 & 3 \\ 2 & 4 & 2 \end{array} \right]\)
Answer: Rank is 1. All 3 columns are linearly dependent
Checking in R.
b <- matrix(c(1,3,2,2,6,4,1,3,2), ncol = 3, nrow = 3)
b
## [,1] [,2] [,3]
## [1,] 1 2 1
## [2,] 3 6 3
## [3,] 2 4 2
rankMatrix(b)
## [1] 1
## attr(,"method")
## [1] "tolNorm2"
## attr(,"useGrad")
## [1] FALSE
## attr(,"tol")
## [1] 6.661338e-16
Compute the eigenvalues and eigenvectors of the matrix A.
Solution:
\(A=\left[ \begin{array}{cccccc} 1 & 2 & 3 \\ 0 & 4 & 5 \\ 0 & 0 & 6 \end{array} \right]\)
\(p_a(x)=Det(A-xI_3)\)
\(=\left[ \begin{array}{cccccc} 1-x & 2 & 3 \\ 0 & 4-x & 5 \\ 0 & 0 & 6-x \end{array} \right]\)
\(=(1-x)*\left[ \begin{array}{cccccc} 4-x & 5 \\ 0 & 6-x \end{array} \right]\)
\(=(1-x)(6-x)(4-x)=(6-x-6x+x^2)(4-x)=(6-7x+x^2)(4-x)=24-28x+4x^2-6x+7x^2-x^3=24-34x+11x^2-x^3\)
Checking in R.
a <- matrix(c(1,0,0,2,4,0,3,5,6), nrow = 3, ncol = 3)
#install.packages("pracma")
library(pracma)
## Warning: package 'pracma' was built under R version 3.5.2
##
## Attaching package: 'pracma'
## The following objects are masked from 'package:Matrix':
##
## expm, lu, tril, triu
b<-charpoly(a)
b
## [1] 1 -11 34 -24
\(x=1,x=6,x=4\)
\(x=1\)
\(=\left[ \begin{array}{cccccc} 0 & 2 & 3 \\ 0 & 3 & 5 \\ 0 & 0 & 5 \end{array} \right]\rightarrow\) \(R3\times0.2\), \(R2-5\times R3\), \(R1-3\times R3\)
\(=\left[ \begin{array}{cccccc} 0 & 2 & 0 \\ 0 & 3 & 0 \\ 0 & 0 & 1 \end{array} \right]\rightarrow\) \(R2\times (1/3)\), \(R1-2\times R2\)
\(=\left[ \begin{array}{cccccc} 0 & 0 & 0 \\ 0 & 1 & 0 \\ 0 & 0 & 1 \end{array} \right]\)
\(\varepsilon_A(1)=\left\langle\Bigg\{\begin{bmatrix}1 \\ 0 \\ 0\end{bmatrix}\ \Bigg\}\right\rangle\)
\(x=6\)
\(=\left[ \begin{array}{cccccc} -5 & 2 & 3 \\ 0 & -2 & 5 \\ 0 & 0 & 0 \end{array} \right]\) \(R2\times-0.5\), \(R1-2\times R2\)
\(=\left[ \begin{array}{cccccc} -5 & 0 & 8 \\ 0 & 1 & -2.5 \\ 0 & 0 & 0 \end{array} \right]\rightarrow\) \(R1\times -0.2\)
\(=\left[ \begin{array}{cccccc} 1 & 0 & -1.6 \\ 0 & 1 & -2.5 \\ 0 & 0 & 0 \end{array} \right]\)
\(\varepsilon_A(1)=\left\langle\Bigg\{\begin{bmatrix}16 \\ 25 \\ 10\end{bmatrix}\ \Bigg\}\right\rangle\)
\(x=4\)
\(=\left[ \begin{array}{cccccc} -3 & 2 & 3 \\ 0 & 0 & 5 \\ 0 & 0 & 2 \end{array} \right]\rightarrow\) \(R3\times0.5\), \(R2-5\times R3\), \(R1-3\times R3\)
\(=\left[ \begin{array}{cccccc} -3 & 2 & 0 \\ 0 & 0 & 0 \\ 0 & 0 & 1 \end{array} \right]\rightarrow\) \(R1\times -(1/3)\)
\(=\left[ \begin{array}{cccccc} 1 & -2/3 & 0 \\ 0 & 0 & 0 \\ 0 & 0 & 1 \end{array} \right]\)
\(\varepsilon_A(1)=\left\langle\Bigg\{\begin{bmatrix} 2 \\ 3 \\ 0 \end{bmatrix}\ \Bigg\}\right\rangle\)
ev <- eigen(a)
ev$values
## [1] 6 4 1
ev$vectors
## [,1] [,2] [,3]
## [1,] 0.5108407 0.5547002 1
## [2,] 0.7981886 0.8320503 0
## [3,] 0.3192754 0.0000000 0