#------------------------------------------------------------------------------------------#
# Comandos:
#          fit.model = ajuste
#          ntot = vetor de replicas
#          attach(dados)
#          source("envelr_bino.txt")
#          ligacao logit
#------------------------------------------------------------------------------------------#
par(mfrow=c(1,1))
X = model.matrix(fit.model)
k = nrow(X)
e = matrix(0,k,100)
tot = numeric(k)
w = fit.model$weights
W = diag(w)
H = solve(t(X)%*%W%*%X)
H = sqrt(W)%*%X%*%H%*%t(X)%*%sqrt(W)
h = diag(H)
td = sort(resid(fit.model, type="deviance")/sqrt(1-h))
#
for(i in 1:100){
for(j in 1:k){
dif = runif(ntot[j]) - fitted(fit.model)[j]
dif[dif>=0] = 0
dif[dif<0]  = 1
tot[j] = sum(dif)}
xmat = cbind(tot,ntot-tot)
fit = glm(xmat ~ X, family=binomial)
w = fit$weights
W = diag(w)
H = solve(t(X)%*%W%*%X)
H = sqrt(W)%*%X%*%H%*%t(X)%*%sqrt(W)
h <- diag(H)
e[,i] = sort(resid(fit, type="deviance")/sqrt(1-h))}
#
e1 = numeric(k)
e2 = numeric(k)
#
for(i in 1:k){
  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="Componente do Desvio", ylim=faixa,pch=16, main="", cex=2, cex.axis=1.5, cex.lab=1.5)
#
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)
#------------------------------------------------------------------------------------------#