library(wooldridge)
library(fastGraph)
library(haven)
hprice1 <- read_dta("C:/Users/USUARIO/Downloads/hprice1.dta")
head(force(hprice1), n=5)
## # A tibble: 5 x 10
## price assess bdrms lotsize sqrft colonial lprice lassess llotsize lsqrft
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 300 349. 4 6126 2438 1 5.70 5.86 8.72 7.80
## 2 370 352. 3 9903 2076 1 5.91 5.86 9.20 7.64
## 3 191 218. 3 5200 1374 0 5.25 5.38 8.56 7.23
## 4 195 232. 3 4600 1448 1 5.27 5.45 8.43 7.28
## 5 373 319. 4 6095 2514 1 5.92 5.77 8.72 7.83
library(fastGraph)
library(stargazer)
options(scipen=99999)
library(stargazer)
modelo_estimado<-lm(formula= price~lotsize+sqrft+bdrms, data = hprice1)
stargazer(modelo_estimado, type="html", title="Modelo estimado")
Modelo estimado
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Dependent variable:
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price
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lotsize
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0.002***
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(0.001)
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sqrft
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0.123***
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(0.013)
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bdrms
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13.853
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(9.010)
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Constant
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-21.770
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(29.475)
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Observations
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88
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R2
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0.672
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Adjusted R2
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0.661
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Residual Std. Error
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59.833 (df = 84)
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F Statistic
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57.460*** (df = 3; 84)
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Note:
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p<0.1; p<0.05; p<0.01
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Coficiente desviacion p_values
library(fastGraph)
# matriz de coeficientes
matriz_coeficiente<-summary(modelo_estimado)$coefficients
t_valores<-matriz_coeficiente[, "t value"]
etiqueta<-names(t_valores)
prueba t
for(j in 2:4){
tc<-t_valores[j]
t_vc<-shadeDist( c(tc), "dt", 3, col=c("black", "yellow"), sub=paste("parametro de la variable:", etiqueta[j]))
print(confint(modelo_estimado, parm=j, level =0.95))
}
## 2.5 % 97.5 %
## lotsize 0.000790769 0.003344644
## 2.5 % 97.5 %
## sqrft 0.09645415 0.1491022
## 2.5 % 97.5 %
## bdrms -4.065141 31.77018
Grafica del valor critico
library(fastGraph)
shadeDist(qchisq(0.05, 88, lower.tail = FALSE), ddist = "dchisq", parm1 = 88, lower.tail = FALSE)
Grafico prueba z
shadeDist()
Prueba F
f<-summary(modelo_estimado)$fstatistic[1]
gl_num<-summary(modelo_estimado)$fstatistic[2]
gl_den<-summary(modelo_estimado)$fstatistic[3]
f_vc<-qf(0.95,gl_num, gl_den, lower.tail=TRUE)
shadeDist(xshade=f,"df",gl_num, gl_den, lower.tail = FALSE, sub=paste("vc:",f_vc,"fc", f))
grafica para p-value
library(fastGraph)
shadeDist(80, ddist = "dchisq",parm1 = 80, lower.tail = FALSE, col=c("black","gray"), sub=paste(c(qchisq(0.05, 80, lower.tail=FALSE))))
