######################################################################
# R commands           Stat 704 
# More Topics in R     University of South Carolina
######################################################################
# This file contains the R commands for the lab.
#
# Lines beginning with the symbol '#' are comments in R.  All other
# lines contain code.
#
# In R for Windows, you may wish to open this file from the menu bar
# (File:Display file); you can then copy commands into the command
# window.  (Use the mouse to highlight one or more lines; then
# right-click and select "Paste to console".)
######################################################################


## review 
## objects
## for loops 
## writing functions 




################## export figure 

pdf(file="/Users/yen-yiho/Desktop/test.pdf")
plot(1:10, 1:10, pch=16)
dev.off()


################# par


op<-par()


y<-rnorm(100)
par(mfrow=c(1,3))

hist(y, xlab="Standard normal distribution", breaks=seq(from=-4, to=4, by=1), main="Centered Title")
par(adj=0)
hist(y, xlab="Standard normal distribution", breaks=seq(from=-4, to=4, by=1), main="Left Justified Title")
par(adj=1)
hist(y, xlab="Standard normal distribution", breaks=seq(from=-4, to=4, by=1), main="Right Justified Title")

par(op)


##############################
## if..else
##################### 
standard<-TRUE
m=4
v=8
if (standard) {
	y<-rnorm(100)
	hist(y)
	m1<-mean(y)
	v1<-var(y)
}	else {
	y<-rnorm(100, mean=m, sd=sqrt(v))
	hist(y)
	m1<-mean(y)
	v1<-var(y)
}

##############################
## ifelse
##################### 

y<-runif(100)
trt<-ifelse(y<0.5, 1, 0)
trt
table(trt)

##############################
## for loops
##################### 
x<-runif(10)

for(i in x){
	print(i)
} 


##############################
# for loops & ifelse
##############################

for (i in 1:10){
	if (i > 5){
		print(i)
	}
}
## if .. else 
x<-rnorm(10, mean=5, sd=1)

for (i in x){
	if (i < 5){
		msg<-paste(i, " is equal or less than 5", sep="")
		print(msg)
	} else {
		msg<-paste(i, " is larger than 5", sep="")
		print(msg)
	}
	
}


##############################
# CLT
##############################

y1<-rep(NA, 100)

for(j in 1:length(y1)){
	y1[j] <-mean(rnorm(100, mean=3, sd=2))
}
y2<-rep(NA, 100)

for(j in 1:length(y2)){
	y2[j] <-mean(rnorm(10, mean=3, sd=2))
}


plot(density(y2), col=2, lty=3, lwd=4, ylim=c(0,2))
lines(density(y1), col=3, lwd=4)


hist(y1)
var(y1)

hist(y2)
var(y2)

##############################
# apply, sapply, lappy 
##############################
### apply 
##############################
m<-matrix(1:20, nrow=10, ncol=2) ## create a matrix of 10 rows x 2 columns
apply(m, 1, mean) ## mean of the rows: rowMeans
apply(m,2, mean)  ## mean of the columns: colMeans 

myfun<-function(x){
	ans<-x^2
	return(ans)
}
##############################
###### sapply 
##############################
x<-1:10
sapply(x, myfun)
#####alternative 
sapply(x, function(x) x^2)
####
myid<-paste("ID-", round(runif(10),2)*100, sep="")
strsplit("ID-11", split="-")

sapply(myid, strsplit, split="-")


mystrsplit<-function(x){
	ans<-strsplit(x, split="-")[[1]][2]
	return(ans)
}

numid<-sapply(myid, mystrsplit)
names(numid)<-NULL
myid


##############################
###### lapply 
##############################

x <- list(a = 1:10, beta = exp(-3:3), logic = c(TRUE,FALSE,FALSE,TRUE))
sapply(x, quantile)


A<-matrix(1:9, nrow=3)
B<-matrix(4:12, nrow=3)
C<-matrix(rep(c(8,9,10), 2), ncol=2)

MyList<-list(A,B, C)
lapply(MyList,"[", 1, 2)
lapply(MyList, "[", , 2)
lapply(MyList, "[",1 , )
A
B
C

##############################
###### Bootstrap 
##############################

varbs<-function(x, B=200){
	bsmean<-rep(0, B)
	len<-length(x)
	for(i in 1:B){
		bsmean[i]<-mean(sample(x, len, replace=T))
	}
	genmean<-mean(bsmean)
	bsvar<-sum((bsmean-genmean)^2/(B-1))		
	return(bsvar)
}

x<-rnorm(100)
varbs(x)