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