1070416Exercise in class

EX1:example for this problem,then eliminate the for loop in the code segment

dta <- read.table("hs0.txt", h=T)#讀入資料
dta.asian <- subset(dta, race=="asian")#把亞洲人之資料提取
r0 <- cor(dta.asian$math, dta.asian$socst)#取相關
cnt <- 0
i<-1
nIter <-1001 #重復做1001次
repeat{
  new <- sample(dta.asian$read)
  r <- cor(new, dta.asian$math)
  i=i+1
  if ( r0 <= r ) cnt <- cnt+1
  if (i>=nIter)
    break
}
cnt/nIter 

## [1] 0.03596404

輸出的結果,感覺有點像老師今天講的用電腦取P值

EX2:example What does the R script do and Replace the “while” loop in the code.

顯示出每次隨機的x,y的散布圖

Brownian <- function(n = 11, pause = 0.05, nIter = 1, ...) {
    x = rnorm(n)
    y = rnorm(n)
    i = 1
    repeat {
      plot(x, y, ...)
      text(x, y, cex = 0.5)
      x = x + rnorm(n)
      y = y + rnorm(n)
      Sys.sleep(pause)
      i = i + 1
      if(i >= nIter) break
    }
} 
Brownian(xlim = c(-20, 20), ylim = c(-20, 20), 
    pch = 21, cex = 2, col = "cyan", bg = "lavender") 

EX3:矩陣調整

library("magrittr")
newsim<- function(n){
  m <- matrix(nrow=n, ncol=2) 
  m[, 1] <- runif(n)
  m[, 2] <- rnorm(n)
Gender <- ifelse(m[, 1]<0.505, "Male", "Female")
Height <- ifelse(m[, 1]<0.505, 170 + 7*m[, 2],160 + 5*m[, 2]) %>% round(2)
Person <- data.frame(Gender,Height)
return(Person)
}

newsim(10)

##    Gender Height
## 1  Female 165.20
## 2  Female 154.27
## 3    Male 165.14
## 4  Female 161.62
## 5  Female 157.48
## 6    Male 169.50
## 7  Female 158.68
## 8  Female 149.99
## 9    Male 173.24
## 10   Male 176.26