R Language
R is a free software environment for statistical computing and graphics.
For a long time I’ve been wondering why we are not able to use Enter in the LyX Scrap environment which was set up by Gregor Gorjanc for Sweave. Two weeks ago, I (finally!) could not help asking Gregor about this issue, as I’m using “LyX + Sweave” more and more in my daily work. He explained it here: LyX-Sweave: mandatory use of control+enter in code chunks
After digging into the LyX customization manual for a while, I found a solution which allows us to press the Enter key just as we normally do when typing in a LyX document. The key is to use Environment instead of paragraph as LatexType for the style definition of Scrap. Besides, I used the LatexName as wrapsweave, as a LatexName is required by LyX. The definition for wrapsweave is simple: just two empty lines by \par. (If you define it as \newenvironment{wrapsweave}{}{}, you will run into troubles sometimes; especially when you use indent for paragraphs.)
As we know, LaTeX environment cannot be centered in LyX (only paragraphs can), so I defined a special environment ScrapCenter when I want to insert graphics via Sweave and make them center-aligned.
I have to admit that the previous post on Christmas is actually not much fun. Today I received another pResent from Yixuan which is more interesting:
Life should be fun. I saw a post in R-help list saying Merry Christmas to other useRs, and I followed up by some R code which can produce a naive animation like this:
Here is the code to generate the above Flash animation with shining Christmas:
library(animation)
saveSWF({
n = length(speed <- runif(angle <- runif(x <- strsplit("MERRY CHRISTMAS",
"")[[1]], 0, 360), 0, 15))
for (j in 1:300) {
angle = angle + speed
plot.new()
plot.window(c(1, n), c(0, 1))
for (i in 1:n) text(i, 0.5, x[i], srt = angle[i], cex = runif(1,
1, 4), col = sample(colors(), 1))
text(n, 0, "Yihui @ 2009-12-24 (http://yihui.name)",
adj = c(1, 0), col = "white", cex = 0.8)
}
}, interval = 0.04, dev = "pdf", outdir = getwd(), para = list(mar = rep(0,
4), bg = "black"), width = 8, height = 1)
## in animation package (>=1.1-0), see demo('Xmas')
There are other animation formats in the R package animation:
- use
saveMovie()to get a GIF animation (need ImageMagick) ani.start()andani.stop()can produce an HTML page with the animation in itsaveLatex()can embed an animation into a PDF document
Since animation 1.0-9, we will be able to create a PDF document with an animation embedded in it; the function is saveLatex(), and its usage is similar to saveMovie() and saveSWF(): you pass an R expression for creating animations to this function, and this expression will be evaluated in the function; the image frames get recorded by a graphics device. In the end, a LaTeX document is written in a directory, and we can get a PDF document by running pdflatex on the document.
In fact, the key point is the LaTeX package named animate, which can be used to insert image frames into a PDF document to generate an animation. The interface of animations created by this package is quite similar to the HTML animation page by the R package animation, moreover, it also uses JavaScript (in PDF) to animate the image frames.
I love R because there are always exciting new packages which can be far beyond your imagination. Here I’d like to introduce a couple of packages that look really awesome:
1. swfDevice: R graphics device for SWF output (by Cameron Bracken)
This package is still at a pre-alpha stage but you can see a sketch now in R-Forge: https://r-forge.r-project.org/projects/swfdevice/
Its author, Cameron, certainly knows well that I will be excited to see it, because I’ve been waiting for a long long time for the REAL Flash animation output in R. What I’ve done in my animation package is simply using SWF Tools to combine several “static” pictures (PNG or PDF, …) into a naive Flash animation — by “naive” I mean there is no interaction or real dynamic stuff in the Flash animation. Hopefully Cameron will provide a useful tool to create genuine Flash animations directly from R (with the help of the library libming).
By the way, I have to mention that the tikzDevice package by Cameron and another author is also fantastic for generating high-quality graphics LaTeX.
Today Romain Francois posted an interesting topic in the R-help list, and you can read his blog post for more details: celebrating R commit #50000. 50000 is certainly not a small number; we do owe R core members a big “thank you” for their great efforts in this fantastic statistical language in the 13 years. When I saw Romain’s data, I suddenly remembered a question I asked to one of Prof Ripley’s student a couple of years ago: does Prof Ripley ever sleep? And he answered “No!”. No wonder we can see Prof Ripley so frequently in the R-help/devel mailing list. If you have stayed on R-help list for enough long time, you’ll surely know several facts, e.g. Martin Maechler will arrive in less than 3 minutes if you dare call an R package “library”, and you will get “Ripleyed” if you are not careful enough in posting your R code.
> library(fortunes)
> fortune("Ripleyed")
And the fear of getting Ripleyed on the mailing list also makes me think, read,
and improve before submitting half baked questions to the list.
-- Eric Kort
R-help (January 2006)
As Sir Francis Bacon said, “Histories make men wise; poets witty; the mathematics subtile; natural philosophy deep; moral grave; logic and rhetoric able to contend.” And Windows stupid.
He should have added the last sentence if he were a Windows user in this age.
1. Avoid Using M$ Excel
A lot of R users often ask this question: “How to import MS Excel data into R?” Well, my suggestion is, avoid using M$ Excel if you are a statistician (or going to be a statistician) because you just cannot imagine how messy Excel data can be: some cells might be merged, some are colored, some texts are bold, several data tables can be put everywhere (e.g. cell(1,1) to (10,4), and (17,3) to (25,9)), stupid bar plots and pie charts are inserted in the sheets, silly statistical procedures that are wrong forever… If you don’t trust my words (yes, I’m a nobody), just read the examples here: Problems with Excel (collected by Prof Harrell).
I know there are reasons for you to continue using Excel. Your boss required you to do so; you don’t have time to learn more about various data formats; everybody is using Excel, and you don’t want to be so cool to use R; or if you finish your tasks too quickly and accurately, your boss will doubt whether you have really spent time on working, hence you will get less money paid (this is a REAL story for me – though I didn’t get less payment, I was indeed doubted when I used R); …
Yanping Chen raised a question in the Chinese COS forum on the output of Eviews: how to (re)format the decimal coefficients in equations as text output? For example, we want to round the numbers in CC = 16.5547557654 + 0.0173022117998*PP + 0.216234040485 * PP(-1) + 0.810182697599 * (WP + WG) to the 3rd decimal places. This can be simply done by regular expressions, as decimals always begin with a “.”. The basic steps are:
- find out where are the decimals in the character string;
- format them;
- replace the original decimals with formatted values;
Given a character vector, we can format the decimals with the code below:
HTH and HTT respectively? (For example, for the sequence HHTH, the number for HTH to appear is 4, and in THTHTT, the number for HTT is 6.)
It seems that the two results are equivalent, as H and T occurs with equal probability 0.5, so we naturally believe the average numbers of steps to HTH and HTT are the same, but the fact is not as we imagined.
## smart guys use math formulae to solve the problem,
## but *lazy* guys like me use simulations with R
coin.seq = function(v) {
x = NULL
n = 0
while (!identical(x, v)) {
x = append(x[length(x) - 1:0], rbinom(1, 1, 0.5))
n = n + 1
}
n
}
set.seed(919)
mean(htt <- replicate(1e+05, coin.seq(c(1, 0, 0))))
# [1] 8.00304
mean(hth <- replicate(1e+05, coin.seq(c(1, 0, 1))))
# [1] 10.0062
png("coin-htt-hth.png", height = 150, width = 500)
par(mar = c(3, 2.5, 0.1, 0), mgp = c(2, 0.8, 0))
boxplot(list(HTT = htt, HTH = hth), horizontal = T,
xlab = "n", ylim = range(boxplot(list(HTT = htt, HTH = hth),
plot = FALSE)$stats))
points(c(mean(htt), mean(hth)), 1:2, pch = 19)
dev.off()
The answer is counterintuitive, isn’t it?
Well, mathematicians certainly do not like my solution (I guess they even hate such an imprecise approach). I hope some smart guys can give me some hints on working out the probability distribution and hence the expectation.
The fire was mainly created by the function image() with carefully designed rows and columns in heated colors heat.colors(). Here is one of the pictures generated from his code:


Recent Comments