load("C:/Users/Logistica4sv/Desktop/ALAN HERNANDEZ/UES 2021/ECONOMETRIA/Guia de trabajo 1/consumption_equation.RData")
n<-nrow(P)
M<-diag(n)-P
residuos<-M%*%C
print(residuos)
## [,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
## 11 7.784083
## 12 -13.127696
## 13 17.521565
## 14 17.304695
## 15 -16.308260
## 16 -5.255508
## 17 2.788211
## 18 -16.379339
## 19 -14.327554
## 20 11.749135
## 21 -31.424669
## 22 -23.329596
## 23 22.171806
## 24 -5.040038
## 25 -36.191398
## 26 -25.211753
## 27 -21.411271
## 28 1.410519
## 29 -24.229564
## 30 20.971808
## 31 43.342653
## 32 36.808458
## 33 17.882297
## 34 -33.100273
## 35 -37.819995
## 36 -49.370820
## 37 23.456143
## 38 -25.510341
## 39 -11.960629
## 40 -9.234201
## 41 21.949616
## 42 3.211123
## 43 -14.511436
## 44 3.197576
## 45 -62.396763
## 46 -66.854500
## 47 8.330745
## 48 91.963380
## 49 61.620735
## 50 48.148861
## 51 -10.717721
## 52 -84.069717
## 53 -56.426627
## 54 125.113605
NUMERAL 2
k<-4
var_error<-t(residuos)%*%residuos/(n-k)
print(var_error)
## [,1]
## [1,] 1428.746
NUMERAL 3
var_error<-as.vector(var_error)
var_cov<-var_error*solve(XX)
print(var_cov)
## (Intercept) Yd W I
## (Intercept) 164.522304918 -9.333540e-02 9.670914e-03 10.5186890800
## Yd -0.093335395 1.891127e-04 -3.276956e-05 -0.0072901023
## W 0.009670914 -3.276956e-05 6.165749e-06 0.0004193421
## I 10.518689080 -7.290102e-03 4.193421e-04 5.3203789879
NUMERAL 4
Consumo_estimado<-P%*%C
cuadro<-as.data.frame(cbind(C,Consumo_estimado,residuos))
names(cuadro)<-c("C","Consumo_estimado","Residuos")
print(head(cuadro))
## C Consumo_estimado Residuos
## 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