even4void

% compile with
%   R CMD Sweave sweave_ggplot.Rnw
%   pdflatex sweave_ggplot.tex
\documentclass[t,ucs,12pt,xcolor=dvipsnames]{beamer}
\usepackage{fancyvrb}

\title{A sample Sweave demo}
\author{Author name}
\date{}

even4void

library(mixOmics)
library(RColorbrewer)

X <- replicate(6, rnorm(50))
X.row.mds <- cmdscale(dist(X), k=1)
X.col.mds <- cmdscale(dist(t(X)), k=1)
cim(cor(X)[order(X.col.mds),order(X.col.mds)], col=rev(brewer.pal(8, "RdBu")))
cim(cor(t(X))[order(X.row.mds),order(X.row.mds)], col=rev(brewer.pal(8, "RdBu")))
cim(X, col=rev(brewer.pal(8, "RdBu"))

even4void

display.cell <- function(x, bgcol="#DAE6F2", ...) {
  opar <- par(bg=bgcol, mar=rep(0,4))
  plot(c(0,1), c(0,1), type="n", axes=FALSE, xlab="", ylab="")
  text(.5, .5, as.character(x), ...)
  lines(c(-0.1,1.1), c(0,0))
  par(opar)
}

format.digits <- function(x) as.character(paste("$", as.character(x), sep="   "))

even4void

@article{arlot2010survey,
	Author = {Arlot, S. and Celisse, A.},
	Journal = {Statistics Surveys},
	Pages = {40--79},
	Title = {A survey of cross-validation procedures for model selection},
	Volume = {4},
	Year = {2010}}

@article{feinerer2008text,
	Author = {Feinerer, I. and Hornik, K. and Meyer, D.},

even4void

x <- seq(0,10)
y <- seq(0,10)
df <- expand.grid(x=x, y=y)
df$z <- rnorm(nrow(df), mean=5)

library(lattice)
levelplot(z ~ x+y, data=df, 
          panel=function(x, y, ...) {
            panel.levelplot(x, y, ...)
            panel.abline(v=1)

even4void

# Time-stamp: <2011-01-07 12:41:47 chl>

#
# Some illustrations of SQL joins with R.
# Inspiration: Jeff Atwood, http://bit.ly/eMhJEp
#

tableA <- data.frame(id=1:4, name=c("Pirate","Monkey","Ninja","Spaghetti"))
tableB <- data.frame(id=1:4, name=c("Rutabaga","Pirate","Darth Vader","Ninja"))

even4void

prologues := 2;

input geometriesyr16;

figure(-u,-u,6.5u,6u);

pair A,B,C,D,E,F,G,H,I,J,K,L,M,N;
picture depart;
numeric i,j,r,v;
r:=.5;

even4void

# Time-stamp: <2010-12-10 14:28:19 chl>

#
# A toy example to illustrate SS idea in the Linear Model.
#

do.it <- function(x, g) {
  stopifnot(is.factor(g))
  stripchart(x ~ g, method="jitter", pch=19, col="darkgrey",
                        vertical=TRUE, ylab="")

even4void

# Some examples of graphical displays for Likert items
#
# Time-stamp: <2010-10-24 20:04:59 chl>
data(Environment, package="ltm")
Environment[sample(1:nrow(Environment), 10),1] <- NA
na.count <- apply(Environment, 2, function(x) sum(is.na(x)))
tab <- apply(Environment, 2, table)/apply(apply(Environment, 2, table), 2, sum)*100

# Cleveland dot plot
dotchart(tab, xlim=c(0,100), xlab="Frequency (%)", sub=paste("N", nrow(Environment), sep="="), pch=19)

even4void

itan <- function(x, keys=NULL, digits=3, no.resp=4) {
  # x is an n subjects by k items matrix
  # keys is a vector with the correct keys (A, B, C, D)
  stopifnot(ncol(x)>1)
  if (is.null(keys)) keys <- rep("A", ncol(x))
  require(ltm)
  raw.resp <- matrix(nr=ncol(x), nc=no.resp)
  colnames(raw.resp) <- LETTERS[1:no.resp]
  for (i in 1:ncol(x)) {
    tmp <- table(x[,i])