416inclass

dta <- read.table("hs0.txt", header=T)
#
dta.asian <- subset(dta, race=="asian")
r0 <- cor(dta.asian$math, dta.asian$socst)
cnt <- 0
nIter <- 1001
for (i in 1:nIter) {
    new <- sample(dta.asian$read)
    r <- cor(new, dta.asian$math)
    if ( r0 <= r ) cnt <- cnt+1
}
cnt/nIter

## [1] 0.03196803

#

改為

i=1
cnt=0
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] 0.04195804

2

每次隨機的x,y的散布圖，照nIter設置的數量產生出多少張圖

Brownian <- function(n = 5, 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") 

改repeat

Brownian <- function(n = 11, pause = 0.05, nIter = 512, ...) {
  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
  }
} 

3

使用ifelse調整m矩陣

library("magrittr")

## Warning: package 'magrittr' was built under R version 3.4.4

newsim<- function(n){
  m <- matrix(nrow=n, ncol=2) 
  m[, 1] <- runif(n)
  m[, 2] <- rnorm(n)
Gender <- ifelse(m[, 1]<0.5, "M", "F")
Height <- ifelse(m[, 1]<0.5, 170 + 7*m[, 2],160 + 5*m[, 2]) %>% round(2)
Person <- data.frame(Gender,Height)
return(Person)
}

newsim(10)

##    Gender Height
## 1       F 165.66
## 2       F 153.11
## 3       F 168.60
## 4       F 160.81
## 5       F 153.15
## 6       M 159.76
## 7       F 171.05
## 8       M 171.02
## 9       M 163.56
## 10      M 169.13