A <- matrix(c(1,2,3,4,
-1,0,1,3,
0,1,-2,1,
5,4,-2,-3), 4, byrow=T)
qr(A)$rank
## [1] 4
The rank is the same as the dimension.
Given an m > n, the maximum rank is n with a non-zero element, the minimum rank is 1.
B <- matrix(c(1,2,1,
3,6,3,
2,4,2), 3, byrow=T)
qr(B)$rank
## [1] 1
The rank is 1.
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), 3, byrow=T)
eigen(A)
## eigen() decomposition
## $values
## [1] 6 4 1
##
## $vectors
## [,1] [,2] [,3]
## [1,] 0.5108407 0.5547002 1
## [2,] 0.7981886 0.8320503 0
## [3,] 0.3192754 0.0000000 0
# Using function to create vectors
vect <- function(x) {
x / sqrt(sum(x^2))
}
l1 <- vect(c(16/25, 1, 2/5))
l2 <- vect(c(2/3, 1, 0))
l3 <- vect(c(1, 0, 0))
eigenvectors <- cbind(l1, l2, l3)
eigenvectors
## l1 l2 l3
## [1,] 0.5108407 0.5547002 1
## [2,] 0.7981886 0.8320503 0
## [3,] 0.3192754 0.0000000 0