Execute the book
1. Generate tikz figures and chapters.tex
  a. Open RStudio
  b. Files > Dropbox > Book > Chap02
  c. Tools > Set Working Directory > To Source File Location
  d. Select lines 7 & 8  (require(tikzDevice); source()) and Run
  e. Sweave2("Chapter02.Rnw")
  f. Repeat a-e for Chapters 3-13
2. Compile PDF for Chapter01, AppendixA, AppendixB
3. latex Main.tex
  a. Comment all includeonly lines
  b. In Terminal window cd Dropbox/Book, type lualatex Main.tex (~ 20 minutes)
  c. Repeat lualatex at least 3 times

Chapter 13: maps, ggplot2, oce, sp, quantreg

Chapter 12: rjags: must install latest version of JAGS from Sourceforge, fields, BMA, sp
rgdal: install from source, maps, maptools, colorRamps, spdep, coda, bootstrap, ggplot2

Chapter 11: maps, spatstat, sp, rgdal, maptools, cluster, xtable

Chapter 10: gamlss, xtable, chron, reshape, ggplot2, network, sna, igraph

Chapter 9: grid, gstat, maptools, sp, rgdal, maps, colorRamps, spdep, spgwr

Chapter 8: quantreg, xtable, ismev, gamlss, gamlss.cens

Chapter 7: pscl, xtable, plotmo, earth

Chapter 6: lubridate, maps, ggplto2, survival, ncdf

Chapter 5: lubridate, maps, classInt, maptools, rgdal, mapdata, ggplot2

Chapter 4: rjags, R2WinBUGS, lattice, LearnBayes

Chapter 3: MASS, ellipse, xtable

Chapter 2: UsingR

Chapter 1: NONE

This will generate the file listings.  Will be examining ways to generate function listings from files. I suggest we use the output from Stangle as parsing may be tough.

setwd("book")
sourcefiles = dir(recursive=TRUE, pattern="*[.][rR]$")
binarydatafiles = dir(recursive=TRUE, pattern="*[.][Rr][dD]ata$")
textdatafiles = dir(recursive=TRUE, pattern="*[.]txt$")

Stangle("Chap02/Chapter02.Rnw")
rnw = dir(pattern="Chapter13.R")
rnwdata = lapply(rnw, function(x) readLines(x))
require(stringr)
funstrings = lapply(rnwdata, function(x) na.omit(str_extract("[0-9a-zA-Z_.]+[(].*[)]", string=x)))

Pick through funstrings by hand and make a list.  Save list by chapter.

Chapter = numeric()
Function = numeric()
for(i in 2:13){
x = read.table(paste("chap",i,"funs.txt", sep=""))
n = length(as.character(unique(x$V1)))
Chapter = c(Chapter, rep(i, n))
Function = c(Function, as.character(unique(x$V1)))
}
x.df = data.frame(Chapter=Chapter, Function=Function)
groups = split(x.df$Chapter, x.df$Function)
str(groups, list.len=1000, vec.len=13)

Copy/paste into text file then edit.  Read the edited file and produce the LaTeX table in AppendixA.rnw.

tbl = table(x.df)



For function calls
rnw = dir(recursive=TRUE, pattern="*[0-9][.][Rr]$")


rnwdata = lapply(rnw, function(x) readLines(x))
require(stringr)
funstrings = lapply(rnwdata, function(x) na.omit(str_extract("[0-9a-zA-Z_.]+[(].*[)]", string=x)))



http://pubs.opengroup.org/onlinepubs/009695399/basedefs/xbd_chap09.html
 
Hope this helps.
We may need to fine tune the POSIX  regular expression (extended) see
 
?regex

require(spatstat)
win = owin(xrange=c(0, 1), yrange=c(0, 1))
x = c(.5, .2, .7)
y = c(.1, .4, .8)
plot(win, main="")
points(x, y, pch=19)
spl = xspline(x, y, shape=-.5, draw=FALSE)
points(spl, pch="+")

n = length(spl$x)
x0 = spl$x[1:(n-1)]
y0 = spl$y[1:(n-1)]
x1 = spl$x[2:n]
y1 = spl$y[2:n]
segs = psp(x0, y0, x1, y1, window=win)
plot(segs, main="")

pts = pointsOnLines(segs, eps=.05)
plot(segs, main="")
plot(pts, add=TRUE, pch="+")

par(mfrow=c(1, 2))
plot(density.psp(segs))
plot(density.ppp(pts))

rpoisppOnLines(100*lengths.psp(segs), segs)
plot(segs, main="")
plot(pts, add=TRUE, pch="+")

require(grid)
hc = grid.circle(r=.05, x=.6, y=.2)
grid.text("h", x=.6, y=.2)
pic = grid.circle(r=.05, x=.4, y=.5)
grid.text(expression(pi), x=.4, y=.5)
nc = grid.circle(r=.05, x=.8, y=.5)
grid.text("n", x=.8, y=.5)
grid.curve(.43, .45, .55, .25, arrow=arrow(type="closed", length=unit(4, "mm")), 
  angle=10, curvature=0, gp=gpar(fill="black"))
grid.curve(.77, .45, .65, .25, arrow=arrow(type="closed", length=unit(4, "mm")), 
  angle=10, curvature=0, gp=gpar(fill="black"))
ac = grid.circle(r=.05, x=.2, y=.8)
grid.text("a", x=.2, y=.8)
bc = grid.circle(r=.05, x=.6, y=.8)
grid.text("b", x=.6, y=.8)
grid.curve(.23, .75, .35, .55, arrow=arrow(type="closed", length=unit(4, "mm")), 
  angle=10, curvature=0, gp=gpar(fill="black"))
grid.curve(.57, .75, .45, .55, arrow=arrow(type="closed", length=unit(4, "mm")), 
  angle=10, curvature=0, gp=gpar(fill="black"))


Reverses axis for plotting...good for Pressure axis
x <- 0:10
set xlim and ylim
set ylim to rev() the range() of 'x'
plot(x, xlim = c(0, 10), ylim = rev(range(x)))


Prevents the output from going beyond the margins
str(ma, strict.width="cut")

Covers grid lines in the legend box
grid()
legend("topleft", lty=1, lwd=2, col=cls, legend=lg, bg="white")

If require is verbose, try switching to library with verbose=FALSE
library(gamlss, verbose=FALSE)

Or better
<<fit gamlss model, echo=TRUE, eval=TRUE, results=hide>>=
library(gamlss)

\section{xspline}

<<plot tracks, echo=FALSE, eval=FALSE, fig=FALSE>>=
plot(brd_lcc, col="gray")
y = slot(dft, "coords")[, 2]
x = slot(dft, "coords")[, 1]
j = rep(1:k, each=3)
for(i in 1:k){
res = xspline(x[j == i], y[j == i], shape=-0.5,
  open=TRUE, draw=FALSE)
nr = length(res$x)
lines(res, lwd=2, col="red")
arrows(res$x[nr - 3], res$y[nr - 3], res$x[nr],
  res$y[nr], lwd=3, length=.07, code=2,col="red")
}
@

The returned tracks are listed by cyclone id.  You flatten the track records by executing the rbind function using the \verb@do.call@ function.
<<execute the rbind function over the list of tracks, echo=TRUE, eval=TRUE>>=
tmp = do.call("rbind", t1$tracks)
@