Calculos de residuos
options(scipen = 99999999)
load("C:/Users/Walter Alemán/Desktop/UES V/ECONOMETRIA/Ejercicios/Ejercicio 5/consumption_equation.RData")
n<-nrow(P)
M<-diag(n)-P
residuos<-M%*%C
print(head(residuos, n=10))
## [,1]
## 1 -5.859103
## 2 2.605057
## 3 45.765735
## 4 31.102448
## 5 -21.037889
## 6 7.008120
## 7 17.859663
## 8 10.705631
## 9 22.002328
## 10 -2.689665
Calculo de la varianza del error
# Sigma Cuadrado
k<-4
Var_error=t(residuos)%*%residuos/(n-k)
print(Var_error)
## [,1]
## [1,] 1428.746
Matriz Var.Cov
Var_error<-as.vector(Var_error)
var.cov<-Var_error*solve(XX)
print(var.cov)
## (Intercept) Yd W I
## (Intercept) 164.522304918 -0.09333539523 0.009670913575 10.5186890800
## Yd -0.093335395 0.00018911268 -0.000032769561 -0.0072901023
## W 0.009670914 -0.00003276956 0.000006165749 0.0004193421
## I 10.518689080 -0.00729010228 0.000419342092 5.3203789879
Estimaciones del Consumo
C_estimado=P%*%C
print(C_estimado)
## [,1]
## 1 982.2591
## 2 995.4949
## 3 979.5343
## 4 1059.7976
## 5 1128.1379
## 6 1135.3919
## 7 1179.3403
## 8 1211.1944
## 9 1288.3977
## 10 1351.4897
## 11 1374.0159
## 12 1406.1277
## 13 1453.1784
## 14 1493.4953
## 15 1557.5083
## 16 1622.5555
## 17 1681.2118
## 18 1801.1793
## 19 1911.9276
## 20 1994.3509
## 21 2097.6247
## 22 2207.5296
## 23 2242.6282
## 24 2322.5400
## 25 2441.3914
## 26 2575.7118
## 27 2697.3113
## 28 2652.2895
## 29 2735.1296
## 30 2847.9282
## 31 2948.7573
## 32 3087.8915
## 33 3185.3177
## 34 3226.1003
## 35 3273.8200
## 36 3324.8708
## 37 3430.8439
## 38 3666.1103
## 39 3832.8606
## 40 3990.4342
## 41 4091.4504
## 42 4276.2889
## 43 4408.2114
## 44 4471.3024
## 45 4528.9968
## 46 4661.3545
## 47 4740.5693
## 48 4836.1366
## 49 5013.9793
## 50 5189.3511
## 51 5434.6177
## 52 5767.7697
## 53 6024.8266
## 54 6132.6864
Cuadro<-as.data.frame(cbind(C, C_estimado, residuos))
names(Cuadro)<-c("C", "C_estimada", "Residuo")
print(head(Cuadro))
## C C_estimada Residuo
## 1 976.4 982.2591 -5.859103
## 2 998.1 995.4949 2.605057
## 3 1025.3 979.5343 45.765735
## 4 1090.9 1059.7976 31.102448
## 5 1107.1 1128.1379 -21.037889
## 6 1142.4 1135.3919 7.008120