statistic-on-air

library(ggplot2)
movies <- movies[1:1000,]

m <- ggplot(movies, aes(x=rating))
m + geom_histogram(binwidth=0.2, colour = "darkgreen", fill = "white", size=1) + geom_rug(aes(y=-2), position="jitter", sides="b")

statistic-on-air

library(ggplot2)
movies <- movies[1:1000,]

m <- ggplot(movies, aes(x=rating))
m + geom_histogram(binwidth=0.2, colour = "darkgreen", fill = "white", size=1) + geom_point(aes(y = -2), position = position_jitter(height = 0.8), size=1)

statistic-on-air

library(ggplot2)

# create fictitious data
a <- runif(10)
b <- runif(12)
c <- runif(7)
d <- runif(15)

# data groups
group <- factor(rep(1:4, c(10, 12, 7, 15)))

statistic-on-air

#Type:
#	(1) wac36 	= Weight-for-age charts, birth to 36 months
#	(2) lac36 	= Length-for-age charts, birth to 36 months
#	(3) wlc 	= Weight-for-recumbent length charts, birth to 36 months
#	(4) hac 	= Head circumference-for-age charts, birth to 36 months
#	(5) wsc 	= Weight-for-stature charts
#	(6) wac20 	= Weight-for-age charts, 2 to 20 years
#	(7) lac20 	= Stature-for-age charts, 2 to 20 years
#	(8) bac 	= BMI-for-age charts, 2 to 20 years
#	(9) bmi.adv	= wac20 + lac20 + bac (for pdf export)

statistic-on-air

#Type:
#	(1) wac36 	= Weight-for-age charts, birth to 36 months
#	(2) lac36 	= Length-for-age charts, birth to 36 months
#	(3) wlc 	= Weight-for-recumbent length charts, birth to 36 months
#	(4) hac 	= Head circumference-for-age charts, birth to 36 months
#	(5) wsc 	= Weight-for-stature charts
#	(6) wac20 	= Weight-for-age charts, 2 to 20 years
#	(7) lac20 	= Stature-for-age charts, 2 to 20 years
#	(8) bac 	= BMI-for-age charts, 2 to 20 years
#

statistic-on-air

PlayTel <- function(x=character){

# load package
require(sound)

# control if the input is a character
if (!is.character(x)) stop("x must be a character")

# split the input
num <- strsplit(as.character(x), "")

statistic-on-air

# Sierra3 dithering

Sierra3Convolution <- function(a){

c <- matrix(0, nrow=dim(a)[1], ncol=dim(a)[2])

for(i in 2:(dim(a)[1]-2)){
for(j in 2:(dim(a)[2]-2)){
	P <- trunc(a[i,j]+0.5)
	e <- a[i,j] - P

statistic-on-air

# Sierra2 dithering

Sierra2Convolution <- function(a){

c <- matrix(0, nrow=dim(a)[1], ncol=dim(a)[2])

for(i in 2:(dim(a)[1]-2)){
for(j in 2:(dim(a)[2]-2)){
	P <- trunc(a[i,j]+0.5)
	e <- a[i,j] - P

statistic-on-air

# Burkes dithering

BurkesConvolution <- function(a){

c <- matrix(0, nrow=dim(a)[1], ncol=dim(a)[2])

for(i in 2:(dim(a)[1]-2)){
for(j in 2:(dim(a)[2]-2)){
	P <- trunc(a[i,j]+0.5)
	e <- a[i,j] - P

statistic-on-air

# Stucki dithering

StuckiConvolution <- function(a){

c <- matrix(0, nrow=dim(a)[1], ncol=dim(a)[2])

for(i in 2:(dim(a)[1]-2)){
for(j in 2:(dim(a)[2]-2)){
	P <- trunc(a[i,j]+0.5)
	e <- a[i,j] - P