similar to: example() and example(package=) like data() and data(package=) ?

[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

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 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(). >

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

I'm sure this is probably simple, but I can't find an answer... I have a data frame (Galton's data on heights of parents and children), in grouped form, parent child frequency 73.5 72.2 1 73.5 73.2 3 72.5 68.2 1 72.5 69.2 2 72.5 70.2 1 72.5 71.2 2 72.5 72.2 7 72.5 73.2 2 72.5 74.2 4 71.5 65.2 1 71.5 66.2 3 71.5 67.2 4 71.5 68.2 3 71.5 69.2 5 71.5 70.2 10 ... and need the ungrouped

[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

Hi I'm trying to make a 3d plot showing a point cloud, the corresponding data ellipse and the principal axes of the ellipse as vectors. library(rgl) data(trees) cov <- cov(trees) mu <- mean(trees) plot3d(trees, type="s", size=0.5, col="blue", cex=2) In this step, an extra box is added. I've tried using box=FALSE, but it has no effect. # how to avoid the

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

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

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

This is probably simple, but I just can't see it... I want to calculate the R^2s for a series of linear models where each term is dropped in turn. I can get the RSS from drop1(), and the r.squared from summary() for a given model, but don't know how to use the result of drop1() to get the r.squared for each model with one term dropped. Working example: library(vcd) # for

Env: Win XP, R 2.9.2] It's a minor annoyance, but I find that after I run example(), the console state of prompting to press Enter for each new graph remains as it is under example. It's more annoying that it seems difficult to turn this behavior off! In a fresh session: > getOption("example.ask") [1] "default" Run an example: > example(plot) plot>

I recently was forced to do a dist-upgrade and rebuild my kernel, so a lot has changed on my system, and I don't know if that is related to the errors & warnings I get from apt-get update. Any ideas? thanks -Michael euclid:~# apt-get update Get: 1 http://debian.yorku.ca stable Release.gpg [378B] Get: 2 http://debian.yorku.ca stable/updates Release.gpg [189B] Get: 3

In using cor(data.frame), it is annoying that you have to explicitly filter out non-numeric columns, and when you don't, the error message is misleading: > cor(iris) Error in cor(iris) : missing observations in cov/cor In addition: Warning message: In cor(iris) : NAs introduced by coercion It would be nicer if stats:::cor() did the equivalent *itself* of the following for a data.frame:

[Using R 2.7.2 on Windows XP] After re-building our heplots package, I've begun to get the following error from sessionInfo(), even though it passes R CMD check and builds without errors: > sessionInfo() Error in x$Priority : $ operator is invalid for atomic vectors In addition: Warning message: In FUN(c("MASS", "heplots", "car", "rgl",

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

I'm looking for something in R to fit a multivariate linear model robustly, using an M-estimator or any of the myriad of other robust methods for linear models implemented in robustbase or methods based on MCD or MVE covariance estimation (package rrcov). E.g., one can fit an mlm for the iris data as: iris.mod <- lm(cbind(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width) ~ Species,

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 <-