poverty.data <- read.table ("http://www.statpower.net/R2101/poverty.dat",header=T)
poverty.data <- na.omit(poverty.data)
attach(poverty.data)
names(poverty.data)

fit <- lm(Infant.Mortality ~ GNP)
plot(GNP,Infant.Mortality)
abline(fit,lty=2,col="red")



my.plot <- function(Lo,Hi,XX,YY){
    if(Lo > Hi){t <- Lo
                Lo <- Hi
                Hi <- t}
    X <- XX[which((XX >= Lo) & (XX <= Hi))]
    Y <- YY[which((XX >= Lo) & (XX <= Hi))]
    plot(X,Y,xlim=c(Lo,Hi))
    if(length(X) < 2)return()
    fit <- lm(Y ~ X)
    abline(fit,lty=2,col="red")
    text((Hi+Lo)/2,.8*max(Y),paste("R.squared = ",round(summary(fit)$r.squared,4),sep=""))
  }

manipulate(my.plot(A,B,GNP,Infant.Mortality),
           A = slider(min(GNP),max(GNP),initial=min(GNP)),
           B = slider(min(GNP),max(GNP),initial=max(GNP))
)

### Block2
GNP.Hi <- GNP[which(GNP >= 3000)]
Infant.Mortality.Hi <- Infant.Mortality[which(GNP >= 3000)]
Country.Hi <- Country[which(GNP >= 3000)]
plot(GNP.Hi,Infant.Mortality.Hi,ylim=c(0,100),xlim=c(0,35000))
rmlist <- identify(GNP.Hi,Infant.Mortality.Hi,labels=Country.Hi)

### Block3
GNP.Hi <- GNP.Hi[-rmlist]
Infant.Mortality.Hi <- Infant.Mortality.Hi[-rmlist]
Country.Hi <- Country.Hi[-rmlist]
plot(GNP.Hi,Infant.Mortality.Hi,ylim=c(0,30))


library(segmented)
out.lm <- lm(Infant.Mortality ~ GNP)  
plot(GNP,Infant.Mortality)
o<-segmented(out.lm,seg.Z=~GNP,psi=list(GNP=c(4000)),
             control=seg.control(display=FALSE))
summary(o)
plot(o,col="red",lty=2,add=TRUE)
  
### Block 4 Remove Region 4 countries
r <- 41:51
GNP.r <- GNP[-r]
Infant.Mortality.r <- Infant.Mortality[-r]
out.lm <- lm(Infant.Mortality.r ~ GNP.r)  
plot(GNP.r,Infant.Mortality.r)
o<-segmented(out.lm,seg.Z=~GNP.r,psi=list(GNP.r=c(4000)),
               control=seg.control(display=FALSE))
summary(o)
plot(o,col="red",lty=2,add=TRUE)
Country.r <- Country[-r]  
identify(GNP.r,Infant.Mortality.r,Country.r) 

# Block 5 Remove Libya as well
r <- c(41:51,75)
GNP.r <- GNP[-r]
Infant.Mortality.r <- Infant.Mortality[-r]
out.lm <- lm(Infant.Mortality.r ~ GNP.r)  
plot(GNP.r,Infant.Mortality.r)
o<-segmented(out.lm,seg.Z=~GNP.r,psi=list(GNP.r=c(4000)),
            control=seg.control(display=FALSE))
summary(o)
plot(o,col="red",lty=2,add=TRUE)
Country.r <- Country[-r]  
identify(GNP.r,Infant.Mortality.r,Country.r) 
 
  
# Block 6
data(segreg)  
attach(segreg)
out.lm <- lm(C~Temp)
  o<-segmented(out.lm,seg.Z=~Temp,psi=list(Temp=c(40)),
               control=seg.control(display=FALSE))
summary(o)
plot(Temp,C)
plot(o,col="red",lty=2,add=TRUE)
identify(Temp,C)

# Block 7
  
Tempr <- Temp[-15]
Cr <- C[-15]
out.lm <- lm(Cr~Tempr)
o<-segmented(out.lm,seg.Z=~Tempr,psi=list(Tempr=c(40)),
             control=seg.control(display=FALSE))
summary(o)
plot(Tempr,Cr)
plot(o,col="red",lty=2,add=TRUE)
identify(Tempr,Cr)