Sea la matriz de covarianzas

S <- matrix(c(3,1,1,1,3,1,1,1,5), nrow= 3, ncol = 3)
S
##      [,1] [,2] [,3]
## [1,]    3    1    1
## [2,]    1    3    1
## [3,]    1    1    5

Matriz simétrica, cuando es igual a su transpuesta//// SACAR NO LO PIDE

B <- t(S)-S
B
##      [,1] [,2] [,3]
## [1,]    0    0    0
## [2,]    0    0    0
## [3,]    0    0    0

Calcular los autovalores y autovectores de la matris S utilizando el lenguaje R

autovalores=eigen(S)
autovalores
## eigen() decomposition
## $values
## [1] 6 3 2
## 
## $vectors
##            [,1]       [,2]          [,3]
## [1,] -0.4082483 -0.5773503  7.071068e-01
## [2,] -0.4082483 -0.5773503 -7.071068e-01
## [3,] -0.8164966  0.5773503 -1.110223e-16

Autovalores de la matriz S

autovalores$values
## [1] 6 3 2

Autovectores de la matriz S

autovectores=eigen(S)$vectors 
autovectores
##            [,1]       [,2]          [,3]
## [1,] -0.4082483 -0.5773503  7.071068e-01
## [2,] -0.4082483 -0.5773503 -7.071068e-01
## [3,] -0.8164966  0.5773503 -1.110223e-16

Multiplicamos para ver si da igual AV1 = lambda1v1

S%*%autovectores[,1:3]
##           [,1]      [,2]          [,3]
## [1,] -2.449490 -1.732051  1.414214e+00
## [2,] -2.449490 -1.732051 -1.414214e+00
## [3,] -4.898979  1.732051 -3.330669e-16

La traza de la matriz

traza = autovalores$values[1] + autovalores$values[2] + autovalores$values[3] 
traza
## [1] 11

La determinate de la matriz

determ = autovalores$values[1] * autovalores$values[2] * autovalores$values[3] 
determ
## [1] 36