#-----------------------------------------------------------------------#
# Comandos:
#        > fit.model <- ajuste
#        > attach(dados)
#        > source("diag_cook_gama")
#-----------------------------------------------------------------------#
X <- model.matrix(fit.model)
n <- nrow(X)
p <- ncol(X)
w <- fit.model$weights
W <- diag(w)
H <- solve(t(X)%*%W%*%X)
H <- sqrt(W)%*%X%*%H%*%t(X)%*%sqrt(W)
h <- diag(H)
library(MASS)
fi <- gamma.shape(fit.model)$alpha
ts <- resid(fit.model,type="pearson")*sqrt(fi/(1-h))
td <- resid(fit.model,type="deviance")*sqrt(fi/(1-h))
di <- (h/(1-h))*(ts^2)
par(mfrow=c(1,1))
#
plot(di,xlab="Índice", ylab="Distância de Cook", pch=16, cex=2, cex.axis=1.5, cex.lab=1.5)
cut = mean(di) + 4*sd(di)
abline(cut,0,lty=2, lwd=2)
identify(di, n=3,cex=2)
#-----------------------------------------------------------------------#