similar to: stats:::biplot.prcomp: Scaling, typo in the help file?

Dear all, I want to use aggregate.formula to conveniently summarize a data.frame. I have quiet some variables in the data.frame and thus I don't want to write all these names by hand, but instead create them on the fly. This approach has the advantage that if there will be even more columns in the data.frame I don't have to change the code. I've hence tried to construct a formula

Dear all, I produced the following graph with ggplot which is almost fine, yet I don't like that the legend for "Means" and "Observations" includes a line, though no line is used in the plot for those two (the line for "Overall Mean" on the other hand is wanted): library(ggplot2) ddf <- data.frame(x = factor(rep(LETTERS[1:2], 5)), y = rnorm(10)) p <-

Dear all, Assume that I have the following data structure: d <- expand.grid(subj=1:5, time=1:3, treatment=LETTERS[1:3]) d$value <- 10 ^ (as.numeric(d$treatment) + 1) + 10 * d$subj + d$time d$value2 <- 100000 + d$value where d$treatment == "C" stands for my control group. What I want to achieve now is to subtract the values corresponding to d$treatment == "C" from

Hi everybody, I'd like to have a list with two elements, where both elements have the same value: z <- list(a=1, b=1) If it happens, that I've to change the value, I've to assure that I change both. This is error prone. Hence, a better way to achieve this is to define: tmp <- 1 z <- list(a=tmp, b=tmp) Now, I'm wondering if it is possible to make this more compact: z

Dear all, I want to get a series of boxplots (grouped by two factors) and I want to overlay the original observations and the following code does almost what I want: library(ggplot) ddf <- data.frame(x=factor(rep(LETTERS[1:4], each=30)), y = runif(120,0,10), grp = factor(rep(rep(1:3, 10), 4))) ggplot(ddf, aes(x, y, colour=grp)) + geom_boxplot() + geom_point() Yet the position of the points

Dear all, I have a very rudimental function which takes a vector of terms and returns a list of all possible models which can be made using the given terms. For example for the set c("1", "x", "y", "x:y") I'd get: ~ 1 ~ x ~ y ~ x:y ~ 1 + x ~ 1 + y ~ 1 + x:y ~ x + y ~ x + x:y ~ y + x:y ~ 1 + x + y ~ 1 + x + x:y ~ 1 + y + x:y ~ x + y + x:y ~ 1 + x + y +

hey, im trying hard to display names (given in a seperate variable) instead of "case numbers" in a pca plot (by biplot of a prcomp output). somebody could help me with this? lukas

Hello, I'd like to reproduce the standard biplot with pc.biplot=TRUE using xyplot in lattice in order to assign different symbols to groupings of observations (similar to the example in fig. 11.2 on page 285 in DAAG). In order to reproduce the biplots I need to know how to scale the observations and variables. In ?biplot.princomp I found that the variables are scaled by 'lambda ^

Dear Experts, May be the problem is still solved, however I tried to find the answer in the archives: I use: > R.version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 1 minor 7.1 year 2003 month 06 day 16

Hi, I'm using: platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 1 minor 5.1 year 2002 month 06 day 17 language R and I would like to apply: > update.packages() trying URL

Hi, I think that the documentation for the biplot function `biplot.princomp' is inconsistent with what it actually does. Here is what the documentation states: pc.biplot If true, use what Gabriel (1971) refers to as a "principal component biplot", with lambda = 1 and observations scaled up by sqrt(n) and variables scaled down by sqrt(n). Then inner products between

Dear all, I have a question about linear models. Is there something comparable to the estimate statement in SAS? E.g. proc mixed data=test; class x1 x2; model y=x1|x2 /s; estimate 'x1' x1 -1 1 x1*x2 -0.5 -0.5 0.5 0.5; estimate 'x2' x2 -1 1 x1*x2 -0.5 0.5 -0.5 0.5; run; Thanks for the help, Dominik Dominik Grathwohl Biostatistician Nestl? Research

> biplot standardGeneric for "biplot" defined from package "stats" function (x, ...) standardGeneric("biplot") <environment: 0x0d4444d8> Methods may be defined for arguments: x Use showMethods("biplot") for currently available ones. > > > showMethods("biplot") Function: biplot (package stats) x="ANY"

Hi, I am trying to understand how the biplot.prcomp is constructed so I can manipulate it to emphasise particular observations and reduce the number of variables shown. The prcomp model I have ran has cor=TRUE and scale=TRUE I have worked out from looking at str(prcomp.model) that... prcomp.model$x = the observations ploted in the biplot prcomp.model$rotation = the variables that form the

I'm attempting to modify how biplot draws its red vectors (among other things). This is how I've started: Biplot <- function(xx, comps = c(1, 2), cex = c(.6, .4)) { ## Purpose: Makes a biplot with princomp() object to not show arrows ## ---------------------------------------------------------------------- ## Arguments: xx is an object made using princomp() ##

Dear all, I'm working with Cox-regression, because data could be censored. But in this particular case not. Now I have a simple example: PRO and PRE are (0,1) coded. The response is not normal distributed. We are interested in a model which could describe interaction. But my results are depending strongly in the choose of the contrast option. It is clear that there is some dependence in

[was sent a wrong R-help address; manually resent by MM] Hello I'am using the 'biplot' and 'biplot.pincomp' functions of the 'mva' package for my studies. The biplot represents both the observations and the variables of a matrix of multivariate data on the same plot. The observations are represented by their numbers (the line of the data matrix), but I would need to

Hello all, I just started in on R today. I am at the point where I am trying to distinguish different groups of data (hydrochemical data) in biplot. I search and found a post about converting the sample number in biplot to a symbol like x or + "> temp <- matrix(runif(50), nrow=10) > temp.pca <- princomp(temp) > biplot(temp.pca, xlabs=c("A", "A",

I have 2 questions about the Biplot function: Both of the questions refer to the following type of graph, which is a biplot of a principal component analysis: biplot(prcomp(dataset)) 1. Does anyone know how to change the appearance of data points on the biplot? As it is currently, for this type of graph, the label for each data point shows up on the graph - does anyone know how to get rid

Dear all, I've been learning biplot (Gabriel, 1971) and some days ago I sent for this list a procedural function with invitation for a collaborative package. Jari Oksanen made some suggestions and I agree with all. So, I reworked the function under the object-oriented programming (OOP/S3). I think it is now a good frame for more resources. Below it is the function and a small script to