The document provides an introduction to the R programming language. It discusses downloading and installing R, using basic functions and operations in R like vectors, matrices, conditional statements, loops, and applying functions. It also lists some online resources for learning more about R including R tips and RjpWiki websites that provide tutorials and documentation on using R.

1. R
sesejun@is.ocha.ac.jp
2009/10/1

2. R
• http://r-project.org/ DL
• Mac, Win, Linux
• S-Plus
•
• Interactive shell
•
• :)

3. • Applications
R
• Version 2.6 (
)
• R project DL
• 1+1[RET]
> 1+1 > 8/3
[1] 2 [1] 2.666667
> 3*6 > as.integer(8/3)
[1] 18 [1] 2
> 3^3 > 8%%3
[1] 27 [1] 2

4. &
> c(1,2,3)
[1] 1 2 3
> x <- 2 > c(1,2,3) + c(4,5,6)
> y <- 3 [1] 5 7 9
> x*y > c(1,2,3) * c(4,5,6)
[1] 6 [1] 4 10 18
> x^y
[1] 8
> c(1,2,3) * 2
[1] 2 4 6
> c(1,2,3) / 2
[1] 0.5 1.0 1.5
> v <- c(1,2,3)
> w <- v + 3
> w
[1] 4 5 6
> v*w
[1] 4 10 18

5. > v <- c(3,2,5,7,2,4,3,1,4)
> length(v)
[1] 9
> max(v)
[1] 7
> min(v)
[1] 1
> mean(v)
[1] 3.444444
> median(v)
[1] 3
> unique(v)
[1] 3 2 5 7 4 1
> sort(v)
[1] 1 2 2 3 3 4 4 5 7
> order(v)
[1] 8 2 5 1 7 6 9 3 4
> hist(v)
> help(max)

6. > v <- c(3,2,5,7,2,4,3,1,4)
> hist(v, main="My First Histgram", col="gray")
> hist(v, col="gray", main="My First Histgram")
> w <- sort(v)
> plot(v,w)
> plot(w,v)

7. > seq(1,4)
[1] 1 2 3 4
> 1:4
[1] 1 2 3 4
> seq(1,5,by=2)
[1] 1 3 5
> rep(1,4)
[1] 1 1 1 1
> rep(1:3,2)
[1] 1 2 3 1 2 3
> v <- c(3,2,5,7,2,4,3,1,4)
> v[1]
[1] 3
> v[c(1,3,5)]
[1] 3 5 2
> v[c(5,3,1)]
[1] 2 5 3
> v[c(F,F,T,T,F,F,T,T,F)]
[1] 5 7 3 1

8. > x <- 3
> x
[1] 3
> x == 3
[1] TRUE
> x == 5
[1] FALSE
> x < 5
[1] TRUE
> v <- c(3,2,5,7,2,4,3,1,4)
> v == c(3,3,3,3,3,3,3,3,3)
[1] TRUE FALSE FALSE FALSE
FALSE FALSE TRUE FALSE FALSE
> v == 3
[1] TRUE FALSE FALSE FALSE
FALSE FALSE TRUE FALSE FALSE
> v < 3
[1] FALSE TRUE FALSE FALSE
TRUE FALSE FALSE TRUE FALSE

9. > v <- c(3,2,5,7,2,4,3,1,4)
> v < 3
[1] FALSE TRUE FALSE FALSE
TRUE FALSE FALSE TRUE FALSE
> v[v<3]
[1] 2 2 1
> v[v>3]
[1] 5 7 4 4
> v[v>3 & v<7]
[1] 5 4 4
> (1:length(v))[v<3]
[1] 2 5 8
> sum(v>3)
[1] 4
> v %in% c(2,3,4)
[1] TRUE TRUE FALSE FALSE
TRUE TRUE TRUE FALSE TRUE
> v[v %in% c(2,3,4)]
[1] 3 2 2 4 3 4

10. > runif(10,min=0,max=1)
[1] 0.45189074 0.15543373 0.04654874 0.56946222 0.06086409
[6] 0.64340708 0.91820279 0.28365751 0.91056890 0.61600679
> n <- 10
> hist(runif(n,min=0,max=1), main=paste("n=",n,sep=""))
> n <- 10000
> hist(runif(n,min=0,max=1), main=paste("n=",n,sep=""))

11. .
> n <- 10
> x <- runif(n,min=0,max=1)
> x
[1] 0.9308879 0.6457174 0.7480667 0.9277555 0.2432229 0.7852049
[7] 0.9005295 0.3948717 0.3442392 0.7808671
> x < 0.3
[1] FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE
> sum(x < 0.3)
[1] 1
> sum(x < 0.3)/n
[1] 0.1
> n <- 10000
> x <- runif(n,min=0,max=1)
> sum(x < 0.3)/n
[1] 0.3013
> n <- 10000
> x <- rnorm(n,mean=0,sd=1)
> sum(x < 0.3)/n
[1] 0.6125
> sum(x > 1.0)/n
[1] 0.1591

12. > m <- matrix((1:9)**2,nrow=3)
> m
[,1] [,2] [,3]
[1,] 1 16 49
[2,] 4 25 64
[3,] 9 36 81
> m[c(2,3),c(2,3)]
[,1] [,2]
[1,] 25 64
[2,] 36 81
> m[2,]
[1] 4 25 64
> m[c(1,2),]
[,1] [,2] [,3]
[1,] 1 16 49
[2,] 4 25 64
> m[,2]
[1] 16 25 36
> m<50
[,1] [,2] [,3]
[1,] TRUE TRUE TRUE
[2,] TRUE TRUE FALSE
[3,] TRUE TRUE FALSE

13. > m <- matrix((1:9)**2,nrow=3)
> solve(m)
[,1] [,2] [,3]
[1,] 1.291667 -2.166667 0.9305556
[2,] -1.166667 1.666667 -0.6111111
[3,] 0.375000 -0.500000 0.1805556
> eigen(m)
$values
[1] 112.9839325 -6.2879696 0.3040371
$vectors
[,1] [,2] [,3]
[1,] -0.3993327 -0.8494260 0.7612507
[2,] -0.5511074 -0.4511993 -0.6195403
[3,] -0.7326760 0.2736690 0.1914866
> v <- c(3,2,5,7,2,4,3,1,4)
> t(v) %*% v
[,1]
[1,] 133

14. R
• R ≠
•
• if for
• R
•
• apply family (
R apply, sapply, lapply )
•
•

15. • R
WEB
• R-Tips:
• http://cse.naro.affrc.go.jp/takezawa/r-tips/r.html
• RjpWiki
• http://www.okada.jp.org/RWiki/
• R