# GLM
# priklad motak zere tetreva
rm(list=ls())
load("motak.RData")

# budeme modelovat pomoci Gamma distribuce, ocistime od nulovych hodnot
cisty <- motak[motak$pomer.zkonzumovanych!=0,]
attach(cisty)

#Vykresleni dat
plot(tetrev.pocty,pomer.zkonzumovanych,pch=20,xlab="pocty tetreva",ylab="pomer zkonzumovanych tetrevu",main="Konzumace tetreva motakem")

# definice GLM modelu
glmmod <- glm(pomer.zkonzumovanych~tetrev.pocty,data=cisty,family=Gamma(link="inverse"))
summary(glmmod)

# vykresleni regresni krivky
t <- seq(from=min(tetrev.pocty),to=max(tetrev.pocty),length.out=100)
lines(t,predict.glm(glmmod,data.frame(tetrev.pocty=t),type="response"),col="red")

# overeni normality residui
plot(glmmod,which=2)
shapiro.test(residuals(glmmod))
detach(cisty)
# -----------------------------------------------------