Propiedades deseables de los estimadores

Mostrar el supuesto de eficiencia, insesgadez (cambiar la semilla ) y consistencia (cambiar el tamaño de muestra) empíricamente (simulación) con 1000 interacciones.

summary(cars)
##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00
set.seed(1)
x=rnorm(20000, 1030000, 200000)
hist(x)

beta1=rnorm(20000,0.3,0.02)
hist(beta1)

beta=runif(20000, 150000,200000)
summary(beta)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  150006  162308  174739  174873  187509  199990
plot(density(beta1), col="Red")

Y=beta+beta1*x
####data.frame
df=data.frame(x,Y)
plot(x,Y)

df=data.frame(Y,x, beta1,beta)
datos=data.frame(Y,x)
head(datos)
##          Y         x
## 1 446293.5  904709.2
## 2 490389.3 1066728.7
## 3 429654.9  862874.3
## 4 537658.7 1349056.2
## 5 529726.5 1095901.6
## 6 444605.8  865906.3

Including Plots

You can also embed plots, for example:

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.