#  Chapter 11

rm(ozone)

ozone.pollution<-read.table("c:\\temp\\ozone.data.txt",header=T)
attach(ozone.pollution)
names(ozone.pollution)

pairs(ozone.pollution,panel=panel.smooth)

library(mgcv)
par(mfrow=c(2,2))
model<-gam(ozone~s(rad)+s(temp)+s(wind))
plot(model)
par(mfrow=c(1,1))

#  make sure that you have down-loaded the tree library from CRAN

library(tree)
model<-tree(ozone~.,data=ozone.pollution)
plot(model)
text(model)

model1<-lm(ozone~temp*wind*rad+I(rad^2)+I(temp^2)+I(wind^2))
summary(model1)

model2<-update(model1,~. – temp:wind:rad)
summary(model2)

model3<-update(model2,~. - wind:rad)
summary(model3)

model4<-update(model3,~. - temp:wind)
summary(model4)

model5<-update(model4,~. - I(rad^2))
summary(model5)

model6<-update(model5,~. - temp:rad)
summary(model6)

model7<-lm(log(ozone) ~ temp + wind + rad + I(temp^2) + I(wind^2))
summary(model7)

model8<-update(model7,~. - I(temp^2))
summary(model8)
plot(model8)

model9<-lm(log(ozone) ~ temp + wind + rad + 
I(wind^2),subset=(1:length(ozone)!=17))
summary(model9)


pollute<-read.table("c:\\temp\\sulphur.dioxide.txt",header=T)
attach(pollute)
names(pollute)

pairs(pollute,panel=panel.smooth)

#  make sure that you have down-loaded the tree library from CRAN

library(tree)
model<-tree(Pollution~.,data=pollute)
plot(model)
text(model)

model1<-lm(Pollution~Temp+I(Temp^2)+Industry+I(Industry^2)+Population+I(Population^2)+Wind+I(Wind^2)+Rain+I(Rain^2)+Wet.days+I(Wet.days^2))
summary(model1)

interactions<-c("ti","tp","tw","tr","td","ip","iw","ir","id","pw","pr","pd","wr","wd","rd")

sample(interactions)

model2<-lm(Pollution~Temp+Industry+Population+Wind+Rain+Wet.days+Wind:Rain+Wind:Wet.days+Industry:Wet.days+Industry:Rain+Rain:Wet.days)

model3<-lm(Pollution~Temp+Industry+Population+Wind+Rain+Wet.days+Population:Rain+Temp:Population+Population:Wind+Temp:Industry+Industry:Wind)

model4<-lm(Pollution~Temp+Industry+Population+Wind+Rain+Wet.days+Temp:Wind+Population:Wet.days+Temp:Rain+Temp:Wet.days+Industry:Population)

model5<-lm(Pollution~Temp+Industry+Population+Wind+Rain+Wet.days+Wind:Rain+Wind:Wet.days+Population:Wind+Temp:Rain)
summary(model5)

model6<-update(model5,~. – Temp:Rain)
model7<-update(model6,~. – Population:Wind)
plot(model7)

model8<-update(model7,~. + Wind:Rain:Wet.days)
summary(model8)