#--------------------------------------------------------------------------------#
# Comandos:
#       fit.model = ajuste
#       attach(dados)
#       source("envel_norm_dglm.txt")
#--------------------------------------------------------------------------------#
par(mfrow=c(1,1))
X =  model.matrix(fit.model)
n =  nrow(X)
p =  ncol(X)
Z=X
require(dglm)
mu =  fitted(fit.model)
fi =  fitted(fit.model$dispersion)
fi1 =  1/fi
Fi = diag(fi1)
H =  sqrt(Fi)%*%X%*%solve(t(X)%*%Fi%*%X)%*%t(X)%*%sqrt(Fi)
h =  diag(H)
r =  resid(fit.model)
td =  (sqrt(fi1)*r)/sqrt(1-h)
#
e =  matrix(0,n,100)
e1 =  numeric(n)
e2 =  numeric(n)
#
for(i in 1:100){
resp1 =  rnorm(n,0,1)
resp1 =  mu + sqrt(fi)*resp1
require(dglm)
fit =  dglm(resp1 ~ X, ~ Z, family=gaussian)
fi2 =  fitted(fit$dispersion)
fi3 =  1/fi2
Fi = diag(fi3)
H =  sqrt(Fi)%*%X%*%solve(t(X)%*%Fi%*%X)%*%t(X)%*%sqrt(Fi)
h =  diag(H)
r =  resid(fit)
e[,i] =  sort((sqrt(fi3)*r)/sqrt(1-h)) 
}
#
for(i in 1:n){
  eo =  sort(e[i,])
e1[i] =  (eo[2]+eo[3])/2
e2[i] =  (eo[97]+eo[98])/2}
#
med =  apply(e,1,mean)
faixa =  range(td,e1,e2)
par(pty="s")
qqnorm(td, xlab="Quantil da N(0,1)",
ylab="Resíduo Studentizado", ylim=faixa, pch=16, main="")
par(new=TRUE)
#
qqnorm(e1,axes=FALSE,xlab="",ylab="",type="l",ylim=faixa,lty=1, main="",lwd=2)
par(new=TRUE)
qqnorm(e2,axes=FALSE,xlab="",ylab="", type="l",ylim=faixa,lty=1, main="",lwd=2)
par(new=TRUE)
qqnorm(med,axes=FALSE,xlab="", ylab="", type="l",ylim=faixa,lty=2, main="",lwd=2)
#--------------------------------------------------------------------------------#