rm(list = ls())
abt <- read.table(
url("http://stat.unm.edu/~fletcher/LLM/DATA/TAB3-1.DAT"),
#"C:\\E-drive\\Books\\ANREG2\\newdata\\TAB21-4.DAT",
#"C:\\E-drive\\Books\\LOGLIN3\\DATA\\Tab3-1.dat",
		  sep="",col.names=c("R","S","A","O","y"))
attach(abt)
abt
#summary(abt)

r=factor(R)
o=factor(O)
s=factor(S)
a=factor(A)

mm <- glm(y ~ r:s:o + o:a ,family = poisson)
mms = summary(mm)

rpearson=(y-mm$fit)/(mm$fit)^(.5)
rstand=rpearson/(1-hatvalues(mm))^(.5)
infv = c(y,mm$fit,hatvalues(mm),rpearson,rstand,
   cooks.distance(mm))
inf=matrix(infv,I(mms$df[1]+mms$df[2]),6,dimnames =
list(NULL,c("n","mhat","lev","Pearson","Stand.","C")))
inf

index=c(1:72)
plot(index,hatvalues(mm),ylab="Leverages",
   xlab="Index")
boxplot(rstand,horizontal=TRUE,
   xlab="Standardized residuals")
plot(index,rstand,ylab="Standardized residuals",
   xlab="Index")
qqnorm(rstand,ylab="Standardized residuals")
boxplot(cooks.distance(mm),horizontal=TRUE,
   xlab="Cook's distances")
plot(index,cooks.distance(mm),ylab="Cook's distances",
   xlab="Index")