setwd("D:/Courses/Statistical Computing/Data/")
setwd("E:/Courses/Statistical Computing/Data/")

rain.data <- read.csv("Rainfall.csv",
header=T,na.strings = "-9")

attach(rain.data)

rain.data

# Assess the correlations.

pairs(cbind(Aco,TelDan,ElRom))
cor(cbind(Aco,TelDan,ElRom))
cor(cbind(Aco,TelDan,ElRom),method=c('spearman'))
cor(cbind(Aco,TelDan,ElRom),method=c('kendall'))


boot.cor <- function(B,x){
  r1 <- NULL
  r2 <- NULL
  n <- nrow(x)
  for (b in 1:B){
    sample.b <- sample(n,n,replace=TRUE)
    x.b <- x[sample.b,]
    r.b <- cor(x.b)
    r1 <- c(r1,r.b[1,3])
    r2 <- c(r2,r.b[2,3])
  }
  return(cbind(r1,r2))
}

out <- boot.cor(500,cbind(Aco,TelDan,ElRom))

hist(out[,1])
hist(out[,2])

hist(out[,1]-out[,2])

qqnorm(out[,2])
qqnorm(log((1+out[,2])/(1-out[,2])))