Libreria fastGraph

Presente unas pequeñas instrucciones para graficar un valor crítico y un “p-value” para las distribuciones Z, T, F, chi^2 y algunos ejemplos gráficos.

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

Estime el modelo

library(stargazer)
options(scipen = 999999)

modelo_hprice1<-lm(formula = price~bdrms+lotsize,data = hprice1)

stargazer(modelo_hprice1,title = "Modelo hprice1",type = "text",digits = 8)

## 
## Modelo hprice1
## ===============================================
##                         Dependent variable:    
##                     ---------------------------
##                                price           
## -----------------------------------------------
## bdrms                     57.31285000***       
##                            (10.88452000)       
##                                                
## lotsize                    0.00285826***       
##                            (0.00090014)        
##                                                
## Constant                    63.26224000        
##                            (39.61957000)       
##                                                
## -----------------------------------------------
## Observations                    88             
## R2                          0.33681690         
## Adjusted R2                 0.32121260         
## Residual Std. Error    84.62413000 (df = 85)   
## F Statistic         21.58486000*** (df = 2; 85)
## ===============================================
## Note:               *p<0.1; **p<0.05; ***p<0.01

Distribución “Z”

library(fastGraph)
shadeDist(qnorm(0.95), "dnorm", 0, 1, col = c("purple","black")) 

shadeDist(qnorm(0.95), lower.tail=FALSE, col = c("purple","black")) 

Distribución “T”

library(stargazer)
#Matriz de Coeficientes 
coeficientes_Modelo<-summary(modelo_hprice1)$coefficients
t_Value<-coeficientes_Modelo[,"t value"]
nombres<-names(t_Value)
for(t in 2:3)
  {
    t_critico<-t_Value[t]
    #Valores Criticos
    print(confint(modelo_hprice1, parm = t,level = 0.90))
  }

##            5 %     95 %
## bdrms 39.21212 75.41358
##                 5 %        95 %
## lotsize 0.001361347 0.004355174

#Grafica Distribucion T
library(fastGraph)
     t_Valor_Critico<- shadeDist( c(-t_critico, t_critico ), "dt", 13,col=c("purple","black"),sub=paste("Parámetro de la Variable:",nombres[t]))

Prueba “F”

F_Anova<-summary(modelo_hprice1)$fstatistic[1]
grados_libertad_num<-summary(modelo_hprice1)$fstatistic[2]
grados_libertad_denom<-summary(modelo_hprice1)$fstatistic[3]
F_Valor_Critico<-qf(0.90,grados_libertad_num,grados_libertad_denom,lower.tail = TRUE)
print(F_Valor_Critico)

## [1] 2.366102

#Grafica Prueba F
library(fastGraph)
shadeDist(xshade = F_Anova,"df",grados_libertad_num,grados_libertad_denom,lower.tail = FALSE, col=c("purple","black"), sub=paste("Valor Critico:",F_Valor_Critico," ","F Critico:",F_Anova))

Distribución Chi^2

library(fastGraph)
shadeDist(qchisq(0.1,25,lower.tail = FALSE),ddist = 'dchisq',parm1 = 25,lower.tail = FALSE, col=c('purple','black'))

shadeDist(23,ddist = 'dchisq',parm1 = 25,lower.tail = FALSE,col=c('purple','black'),sub=paste(c(qchisq(0.1,25,lower.tail = FALSE))))