R NOTE -- learn intro

#display the names of (most of) the objects which are currently stored within R
objects()
ls()

#remove objects
rm(x, y, z, ink, junk, temp, foo, bar)

All objects created during an R session can be stored permanently in a file for use in future R sessions. At the end of each R session you are given the opportunity to save all the currently available objects. If you indicate that you want to do this, the objects are written to a file called ‘.RData’5 in the current directory, and the command lines used in the session are saved to a file called ‘.Rhistory’.

Vectors and assignment

# 3 way of assignment
x <- c(10.4, 5.6, 3.1, 6.4, 21.7)
c(10.4, 5.6, 3.1, 6.4, 21.7) -> x
assign("x", c(10.4, 5.6, 3.1, 6.4, 21.7))

#create vector by vector
y <- c(x, 0, x)

regular sequences

1:15    # got 1,2,3,4...15
2*1:10  # got 2,4,6,8,10,12,...20
seq(1,10) # got 1,2,3,4,5...10
seq(-5, 5, by=.2) -> s3 # got c(-5.0, -4.8, -4.6, ..., 4.6, 4.8, 5.0).

rep(x,times=2)  # got c(1,2,3,4,1,2,3,4)
rep(x,each=2)  # got c(1,1,2,2,3,3,4,4)

Logical vectors

TRUE FALSE NA are logical vector , Logical vectors are generated by conditions

Vectors must have their values all of the same mode.

 temp <- x > 13 # got TRUE or FALSE

 z <- c(1:3,NA); ind <- is.na(z) # got c(FALSE,FALSE,FALSE,TRUE)

Intrinsic attributes: mode and length

Model

 logical, numeric, complex, character or raw.

c("1",1) # got c("1","1") charactor mode
#change mode
z <- 1:3 
digits <- as.character(z) # got c("1","2","3")
as.integer(digits) # got 1:3

empty vector

numeric(0) # model numeric
character(0) # mode character

Length

recursive structures

list,function and expression

attributes

attributes(x) # got all attributes
attr(x,"name") # got attribute by name
attr(x,"name")<-value # set attribute value on name

Arrays and matrices

create n-dimension array from vector

a = 1:100
dim(a)<-c(10,5,2) # got a 3-dimension vector
# a must have the same length of 10*5*2 in this case
a[1,1,1] # index 0
a[10,1,1] # index 9
a[10,5,1] # index 49
a[10,5,2] # index 99

create 2-dimension array directly

arr <-array(1:20,dim=c(4,5))

 Negative indices are not allowed in index matrices. NA and zero values are allowed

#if h is shorter than 24, its values are recycled from the beginning again to make it up to size 24
vec = 1:10
arr = array(vec,dim=c(4*3)) 
# got
# 1 5 9
# 2 6 10
# 3 7 1
# 4 8 2

outer product

ab <- a %o% b
outer(a,b,"*")

# "*" can be replaced by function
f <- function(x, y) cos(y)/(1 + x^2) 
z <- outer(x, y, f)

transpose of A

t(x)
aperm(x, c(2,1))

矩阵乘法

x %*% y

diag(p) , if p is diagnal entries get a matrix , if p is matrix get a diagonal entries

diag(v) # get a diagonal matrix
diag(M) # get the main diagonal entries

Linear equations and inversion

b <- A %*% x
solve(A,b)

eigenvalues # 特征值
eigenvectors # 特征向量
symmetric #对称

Eigenvalues and eigenvectors

ev <- eigen(Sm)
evals <- eigen(Sm)$values
evals <- eigen(Sm)$vectors
evals <- eigen(Sm, only.values = TRUE)$values
evals <- eigen(Sm, only.values = TRUE)$values

Singular value decomposition & determinants

orthonormal

Lists

Lst <- list(name="Fred", wife="Mary", no.children=3, child.ages=c(4,7,9))
Lst[1] 
Lst[2]
Lst[3]
Lst[4]

Lst$name 
Lst$wife
Lst$no.children
Lst$child.ages

Lst[["name"]] 
Lst[["wife"]] 
Lst[["no.children"]] 
Lst[["child.ages"]] 

Data frames

A data frame is a list with class "data.frame".

‘...’ argument

Another frequent requirement is to allow one function to pass on argument settings to another. For example many graphics functions use the function par() and functions like plot() allow the user to pass on graphical parameters to par() to control the graphical output.

fun1 <- function(data, data.frame, graph=TRUE, limit=20, ...) {
   [omitted statements]
   if (graph) 
      par(pch="*", ...)
   [more omissions]
}