Problem Set 1
A <- matrix(c(1,2,3,4,-1,0,1,3,0,1,-2,1,5,4,-2,-3),nrow=4,ncol=4, byrow=TRUE)
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
y<- qr(A)
y$rank
## [1] 4
Answer: The maximum rank is n and minimum rank is 1 if the matrix is non-zero.
A <- matrix(c(1,2,1,3,6,3,2,4,2),nrow=3,ncol=3, byrow=TRUE)
A
## [,1] [,2] [,3]
## [1,] 1 2 1
## [2,] 3 6 3
## [3,] 2 4 2
y<- qr(A)
y$rank
## [1] 1
Problem Set 2
Compute the eigenvalues and eigenvectors of the matrix A. You’ll need to show your work. You’ll need to write out the characteristic polynomial and show your solution.
A <- matrix(c(1,2,3,0,4,5,0,0,6),nrow=3,ncol=3, byrow=TRUE)
A
## [,1] [,2] [,3]
## [1,] 1 2 3
## [2,] 0 4 5
## [3,] 0 0 6
I <- diag(x=1,nrow=3, ncol=3)
#eigenvalues
#det(A - x*I) = 0
#(1-x)*(4-x)*(6-x)=0
x1=1
x2=4
x3=6
#test eigenvalues
det(A - x1*I)
## [1] 0
det(A - x2*I)
## [1] 0
det(A - x3*I)
## [1] 0
#eigenvetors
library("pracma")
## Warning: package 'pracma' was built under R version 3.4.3
#x1=1
m1<-A-x1*I
rref(m1)
## [,1] [,2] [,3]
## [1,] 0 1 0
## [2,] 0 0 1
## [3,] 0 0 0
# N(A - x1*I) = c(1,0,0)
#x2=4
m2<-A-x2*I
rref(m2)
## [,1] [,2] [,3]
## [1,] 1 -0.6666667 0
## [2,] 0 0.0000000 1
## [3,] 0 0.0000000 0
# N(A - x2*I) = c(0.66667,1,0)
#x3=6
m3<-A-x3*I
rref(m3)
## [,1] [,2] [,3]
## [1,] 1 0 -1.6
## [2,] 0 1 -2.5
## [3,] 0 0 0.0
# N(A - x3*I) = c(1.6,2.5,1)