library(wooldridge)
data(hprice1)
head(force(hprice1),n=5)
## price assess bdrms lotsize sqrft colonial lprice lassess llotsize lsqrft
## 1 300 349.1 4 6126 2438 1 5.703783 5.855359 8.720297 7.798934
## 2 370 351.5 3 9903 2076 1 5.913503 5.862210 9.200593 7.638198
## 3 191 217.7 3 5200 1374 0 5.252274 5.383118 8.556414 7.225482
## 4 195 231.8 3 4600 1448 1 5.273000 5.445875 8.433811 7.277938
## 5 373 319.1 4 6095 2514 1 5.921578 5.765504 8.715224 7.829630
library(wooldridge)
library(stargazer)
##
## Please cite as:
## Hlavac, Marek (2022). stargazer: Well-Formatted Regression and Summary Statistics Tables.
## R package version 5.2.3. https://CRAN.R-project.org/package=stargazer
modelo_precio<-lm(formula = price~lotsize+sqrft+bdrms, data=hprice1)
stargazer(modelo_precio,title = "modelo precio",type="text")
##
## modelo precio
## ===============================================
## Dependent variable:
## ---------------------------
## price
## -----------------------------------------------
## lotsize 0.002***
## (0.001)
##
## sqrft 0.123***
## (0.013)
##
## bdrms 13.853
## (9.010)
##
## Constant -21.770
## (29.475)
##
## -----------------------------------------------
## Observations 88
## R2 0.672
## Adjusted R2 0.661
## Residual Std. Error 59.833 (df = 84)
## F Statistic 57.460*** (df = 3; 84)
## ===============================================
## Note: *p<0.1; **p<0.05; ***p<0.01
library(fastGraph)
library(wooldridge)
library(lmtest)
## Loading required package: zoo
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
prueba_white<-bptest(modelo_precio,~I(lotsize^2)+I(sqrft^2)+I(bdrms^2)+(lotsize*sqrft)+(lotsize*bdrms)+(sqrft*bdrms),data=hprice1)
print(prueba_white)
##
## studentized Breusch-Pagan test
##
## data: modelo_precio
## BP = 33.732, df = 9, p-value = 9.953e-05
#Se rechaza H0, por lo tanto, hay evidencia de que la varianza de los residuos no es homocedastica
library(lmtest)
library(stargazer)
u_i<-modelo_precio$residuals
datos_pb<-as.data.frame(cbind(u_i,hprice1))
rg<-lm(I(u_i^2)~lotsize+sqrft+bdrms+I(lotsize^2)+I(sqrft^2)+I(bdrms^2)+lotsize*sqrft+lotsize*bdrms+sqrft*bdrms,data = datos_pb)
sumario<-summary(rg)
n<-nrow(datos_pb)
R_2<-sumario$r.squared
lm_w<-n*R_2
gl=length(terms(rg))
p_value<-1-pchisq(q = lm_w,df = gl)
vc<-qchisq(p = 0.95,df = gl)
salida_white<-c(lm_w,vc,p_value)
names(salida_white)<-c("lmw","Valor Crítico","P value")
stargazer(salida_white,title = "Resultados prueba White",type = "text",digits = 6)
##
## Resultados prueba White
## =================================
## lmw Valor Crítico P value
## ---------------------------------
## 33.731660 7.814728 0.0000002
## ---------------------------------
library(fastGraph)
shadeDist(xshade = lm_w,
ddist = "dchisq",
parm1 = lm_w,
lower.tail = FALSE)
