Y<-matrix(data = c(30,20,36,24,40),
nrow = 5,
ncol = 1,byrow = TRUE)
colnames(Y) <-c("Y")
print(Y)
## Y
## [1,] 30
## [2,] 20
## [3,] 36
## [4,] 24
## [5,] 40
X<-cbind(rep(x=1,5),
matrix(data = c(4,10,3,8,6,11,4,9,8,12),
nrow = 5,
ncol = 2,
byrow = TRUE))
colnames(X)<-c("Cte", "X1","X2")
print(X)
## Cte X1 X2
## [1,] 1 4 10
## [2,] 1 3 8
## [3,] 1 6 11
## [4,] 1 4 9
## [5,] 1 8 12
library(readr)
library(dplyr)
archivo<-"D:/ejercicio_doss.csv"
datos<-read_csv(file = archivo)
Y_<-datos %>% select("Y") %>% as.matrix()
temp<-
X_<-datos %>% mutate(Cte=1) %>% select("Cte","X1", "X2") %>% as.matrix()
print(X_)
## Cte X1 X2
## [1,] 1 5 7.14
## [2,] 1 53 5.10
## [3,] 1 60 4.20
## [4,] 1 63 3.90
## [5,] 1 69 1.40
## [6,] 1 82 2.20
## [7,] 1 100 7.00
## [8,] 1 104 5.70
## [9,] 1 113 13.10
## [10,] 1 130 16.40
## [11,] 1 150 5.10
## [12,] 1 181 2.90
## [13,] 1 202 4.50
## [14,] 1 217 6.20
## [15,] 1 229 3.20
## [16,] 1 240 2.40
## [17,] 1 243 4.90
## [18,] 1 247 8.80
## [19,] 1 249 10.10
## [20,] 1 254 6.70
print(Y_)
## Y
## [1,] 32
## [2,] 450
## [3,] 370
## [4,] 470
## [5,] 420
## [6,] 500
## [7,] 570
## [8,] 640
## [9,] 670
## [10,] 780
## [11,] 690
## [12,] 700
## [13,] 910
## [14,] 930
## [15,] 940
## [16,] 1070
## [17,] 1160
## [18,] 1210
## [19,] 1450
## [20,] 1220
XX<-t(X)%*%X
print(XX)
## Cte X1 X2
## Cte 5 25 50
## X1 25 141 262
## X2 50 262 510
XY<-t(X)%*%Y %>% as.matrix()
print(XY)
## Y
## Cte 150
## X1 812
## X2 1552
XX_inv<-solve(XX)
print(XX_inv)
## Cte X1 X2
## Cte 40.825 4.375 -6.25
## X1 4.375 0.625 -0.75
## X2 -6.250 -0.750 1.00
Beta<-XX_inv%*%XY
colnames(Beta)<-c("parametros")
print(Beta)
## parametros
## Cte -23.75
## X1 -0.25
## X2 5.50
Beta_<-solve(a = XX, b = XY)
colnames(Beta_)<-c("parametros")
print(Beta_)
## parametros
## Cte -23.75
## X1 -0.25
## X2 5.50
-Los autovalores se definen como las raices de Gamma, de la siguiente ecuacion polinomica : C-??*I=0, donde C es una matriz cuadrada -Se usara comado eigen (XX)
autovalores<-eigen(XX)
print(autovalores)
## eigen() decomposition
## $values
## [1] 650.78185037 5.19448432 0.02366531
##
## $vectors
## [,1] [,2] [,3]
## [1,] -0.08623239 0.1629390 0.9828606
## [2,] -0.45874789 -0.8822205 0.1060061
## [3,] -0.88437229 0.4417441 -0.1508239
print(autovalores$values)
## [1] 650.78185037 5.19448432 0.02366531