Edition : the problem in my question was I've tried to find matrix S
from equation 8 but this equation have error.
How to directly obtain right eigenvectors of matrix in R ? 'eigen()' gives only left eigenvectors
Really last edition, I've made big mess here, but this question is really important for me :
eigen()
provides some matrix of eigenvectors, from function help :
" If ‘r <- eigen(A)’, and ‘V <- r$vectors; lam <- r$values’, then
A = V Lmbd V^(-1)
(up to numerical fuzz), where Lmbd =diag(lam)
"
that is A V = V Lmbd
, where V is matrix now we check it :
set.seed(1)
A<-matrix(rnorm(16),4,4)
Lmbd=diag(eigen(A)$values)
V=eigen(A)$vectors
A%*%V
> A%*%V
[,1] [,2] [,3] [,4]
[1,] 0.0479968+0.5065111i 0.0479968-0.5065111i 0.2000725+0i 0.30290103+0i
[2,] -0.2150354+1.1746298i -0.2150354-1.1746298i -0.4751152+0i -0.76691563+0i
[3,] -0.2536875-0.2877404i -0.2536875+0.2877404i 1.3564475+0i 0.27756026+0i
[4,] 0.9537141-0.0371259i 0.9537141+0.0371259i 0.3245555+0i -0.03050335+0i
> V%*%Lmbd
[,1] [,2] [,3] [,4]
[1,] 0.0479968+0.5065111i 0.0479968-0.5065111i 0.2000725+0i 0.30290103+0i
[2,] -0.2150354+1.1746298i -0.2150354-1.1746298i -0.4751152+0i -0.76691563+0i
[3,] -0.2536875-0.2877404i -0.2536875+0.2877404i 1.3564475+0i 0.27756026+0i
[4,] 0.9537141-0.0371259i 0.9537141+0.0371259i 0.3245555+0i -0.03050335+0i
and I would like to find matrix of right eigenvectors R
,
equation which define matrix of left eigenvectors L
is :
L A = LambdaM L
equation which define matrix of right eigenvectors R
is :
A R = LambdaM R
and eigen() provides only matrix V
:
A V = V Lmbd
I would like to obtain matrix R
and LambdaM
for real matrix A
which may be negative-definite.
A worked example.
Default (= right eigenvectors):
m <- matrix(1:9,nrow=3)
e <- eigen(m)
e1 <- e$vectors
zapsmall((m %*% e1)/e1) ## right e'vec
## [,1] [,2] [,3]
## [1,] 16.11684 -1.116844 0
## [2,] 16.11684 -1.116844 0
## [3,] 16.11684 -1.116844 0
Left eigenvectors:
eL <- eigen(t(m))
eL1 <- eL$vectors
(We have to go to a little more effort since we need
to be multiplying by row vectors on the left; if
we extracted just a single eigenvector, R's ignorance
of row/column vector distinctions would make it
"do the right thing" (i.e. (eL1[,1] %*% m)/eL1[,1]
just works).)
zapsmall(t(eL1) %*% m/(t(eL1)))
## [,1] [,2] [,3]
## [1,] 16.116844 16.116844 16.116844
## [2,] -1.116844 -1.116844 -1.116844
## [3,] 0.000000 0.000000 0.000000