similar to: [R-pkgs] GGally - Plot Matrix Extension for GGplot2

GGally: a companion to GGplot2. GGally is a package built to produce plot matrices without the hassle of making viewports and labels yourself. GGally is built upon the GGplot2 framework. Keeping the functionality and feel of ggplot, GGally has shortened common function calls and added a few new ones. ggpairs, the main function within GGally, will take your data set and produce a plots

GGally: a companion to GGplot2. GGally is a package built to produce plot matrices without the hassle of making viewports and labels yourself. GGally is built upon the GGplot2 framework. Keeping the functionality and feel of ggplot, GGally has shortened common function calls and added a few new ones. ggpairs, the main function within GGally, will take your data set and produce a plots

I'm pleased to announce the release of the vcdExtra package, v. 0.5-0 from R-Forge to CRAN, on its way to a CRAN server near you. vcdExtra was originally designed to serve as a sandbox for introducing extensions of mosaic plots and other visualizations for categorical data, particularly those that apply to (poisson surrogate) loglinear models fitted using glm() and related, generalized

Hi, A following function was kindly provided by GGally?s maintainer, Barret Schloerke. function(data, mapping, ...) { p <- ggplot(data = data, mapping = mapping) + geom_point(color = I("blue")) + geom_smooth(method = "lm", color = I("black"), ...) + theme_blank() + theme(panel.border=element_rect(fill=NA, linetype =

I'm working with an historical image that may be (one of?) the first uses of gray-scale shading to show the pattern of values in a matrix/table, later used by Bertin in his 'reorderable matrix' and sometimes called a scalogram. The image is at http://euclid.psych.yorku.ca/SCS/Gallery/images/Private/scalogram.jpg The rows refer to the arrondisements of Paris, the cols to various

I have two series of events over time and I want to construct a graph of the relative frequency/density of these events that allows their distributions to be sensibly compared. The events are the milestones items in my project on milestones in the history of data visualization [1], and I want to compare trends in Europe vs. North America. I decided to use a graph of two overlaid density

In a recent talk ('Visions of the Past, Present & Future of Statistical Graphics'), I talked about, among other things, the lessons Minard's March on Moscow graphic had for modern statistical graphics, and illustrated aspects of power and simplicity in several programming languages where this graphic had been recreated. I referred to 'elegance factors' of various

I'm happy to announce the candisc package, v 0.5-9, now on CRAN. Generalized Canonical Discriminant Analysis Description This package includes functions for computing and visualizing generalized canonical discriminant analyses for a multivariate linear model. They are designed to provide low-rank visualizations of terms in a mlm via the plot method and the heplots package. The methods

I'm happy to announce the candisc package, v 0.5-9, now on CRAN. Generalized Canonical Discriminant Analysis Description This package includes functions for computing and visualizing generalized canonical discriminant analyses for a multivariate linear model. They are designed to provide low-rank visualizations of terms in a mlm via the plot method and the heplots package. The methods

System: [Windows XP Pro, R 2.8.0 and R 2.81.] When I do R graphics on Windows and want .eps output for LaTeX, with *tight bounding boxes* I usually do as follows from Rgui: - Save as Postscript ... myfig.ps - Open myfig.ps in Gsview, select PS to EPS, Save as ... myfig.eps This always worked before, and gave me .eps files that did not include much more white space than I like, didn't

[Environment: WinXp, R 2.9.2, all packages up to date; building under (StatET 0.8, eclipse 3.5.1) or from a batch file] I'm in the process of creating a package, HistData, on R-forge, containing interesting data sets from the history of statistics and data visualization. It contains several examples that use ggplot2, which I've declared as a Suggests: in the DESCRIPTION file. The

The question is how to use a URL in place of a file= argument for read.*.functions that do not support this internally. e.g., utils::read.table() and her family all support a file= argument that can take a URL equally well as a local file. So, if I have a file on the web, I can equally well do > langren <- read.csv("langrens.csv", header=TRUE) > langren <-

I'm trying to test an extension of mosaic() from the vcd package that requires a change to the basic strucplot() function from that package. I want to test my change by sourcing the replacement function into my R session. But when I do that, source("c:/R/mosaics/strucplot-MF.R") and run my extension, it is apparent that it is vcd:::strucplot that is eventually called, not my

How can I read a space-delimited file, where the data values for each case are folded before column 80, and so appear on two lines for each case? The first few cases look like this loc type bio H2S sal Eh7 pH buf P K Ca Mg Na Mn Zn Cu NH4 OI DVEG 676 -610 33 -290 5.00 2.34 20.238 1441.67 2150.00 5169.05 35184.5 14.2857 16.4524 5.02381 59.524 OI DVEG 516 -570 35 -268 4.75 2.66 15.591 1299.19

How can I get the result of, e.g., poly(1:3. degree=2) to give me the unnormalized integer coefficients usually used to explain orthogonal polynomial contrasts, e.g, -1 1 0 -2 1 1 As I understand things, the columns of x^{1:degree} are first centered and then are normalized by 1/sqrt(col sum of squares), but I can't see how to relate this to what is returned by poly(). >

Hi, You can so something like this XX <- data.frame(x=1:10,y=rbinom(10,3,0.5)) sapply(XX,rep,XX[,2]) HTH (if this do what you really want) Thomas -----Urspr?ngliche Nachricht----- Von: Michael Friendly [mailto:friendly at yorku.ca] Gesendet: Do 25.09.2003 19:14 An: r-help Cc: Betreff: [R] ungrouping grouped data I'm sure this is probably simple, but I can't find

[Env: WinXp, R 2.9.2] In my .Rprofile, I define a number of utility functions I'd like to have available in my R session, but don't want them to be *normally* listed by ls(), or more importantly, saved if I save my session variables/functions. How can I do this? -- Michael Friendly Email: friendly AT yorku DOT ca Professor, Psychology Dept. York University Voice: 416

In a package I'm working on there is a vignette with a number of graphs that result in huge .pdf files, so the .pdf for the vignette is around 17 Mb. If these graphs are converted to .png, and the .tex file is compiled with pdflatex, the resulting .pdf is ~1 Mb. I'm reluctant to put the .Rnw file into the package as is, generating the huge .pdf for the vignette. I first tried

The Institute for Social Research (ISR) and its Statistical Consulting Service (SCS) at York University are pleased to announce our Summer Program In Data Analysis (SPIDA) for 2012. The Program runs from May 24th to June 1st, 2012.This year?s Program focuses on the theory and practice of linear models and mixed [or multilevel] models, as they are applied to hierarchical and longitudinal data.

[Env: Win XP Pro / R 2.11.1] I keep occasionally running into the annoying problem of getting warnings from R CMD check regarding non ASCII characters in .Rd files, without any easy way of finding them. Mostly these come from copy/paste of references or other material from web pages or Win applications, and often involve varieties of quote-like characters, e.g., if I try to include output