similar to: Options to plot.mca ?

Andy, Take a look at Greenacre, Theory and Applications of Correspondence Analysis. He has many example of dealing with all sorts of data. Basically, the technique is relevant for 2-way tables -- MCA is an extenstion. It is not clear in your example whether CA is really appropriate -- you want to make an observation (if at all possible) fall in one cell, treating the others layers as

Greetings, again. This is not strictly an R question, so please feel free to ignore it if you like. My question is about the substance of correspondence analysis. Specifically, is it appropriate to use ca on a matrix of values such that the columns and/or rows are not mutually exclusive? To be more detailed: - The standard use of ca is illustrated in the example of corresp() (from MASS):

Can anyone explain this behavior? Essentially, I've created a short file to be read in via source() that gets some descriptive information on a series of variables in a data frame. For each variable, I do three things: print('last.hc.actors') quantile(last.hc.actors,probs=seq(0,1,0.1),na.rm=T) stem(last.hc.actors) where the variable name is (in this case) last.hc.actors. All that

Greetings - In trying to do a multiple correspondence analysis, I need to coerce a data frame such that each of its columns will be a factor. Can someone offer advice on how to make this happen? I've tried this: > logic.resources.f.df<-apply(logics.resources.df, 2, factor) but: > is.factor(logic.resources.f.df$interests) [1] FALSE I've also tried individually, >

Greetings- I've got some plots I'd like to include in a LaTeX document; specifically, I'd like to include them via pictex() so I can edit some of the particulars directly. However, an odd problem is coming up: a diagonal line is drawn from bottom-left to upper-right when using pictex(). This does not happen using X11() or postscript() with the same series of commands. Any ideas why

Greetings- I'm aware that there's no documentation for pictex available easily (that is, without purchasing it). I'm wondering if someone can help me with a simple task. When generating a plot using pictex() from R, one of the commands I use is mtext("Dimension 2: L=xxxx", side=2, line=3) when using X11(), this appears vertically along the Y axis; when using pictex(), it

Greetings. I'm about to embark on my first big (to me at least!) R project, which will be to write a function to plot three-dimensional multiple correspondence analysis (mca) plots in a manner similar to scatterplot3d(). (plot.mca() plots only two dimensions, even though mca() will calculate more.) Before I do so, however, I would love to know that I'm not reinventing the wheel or any

I've attached a perl script that I wrote to build smbpasswd from /etc/passwd. Please note that this writes a samba-2.0 format smbpasswd file. This script will: # - create accounts that exist in /etc/passwd and not in smbpasswd # - remove accounts that exist in smbpasswd and not in /etc/passwd # - preserve existing password, flags and LCT fields in smbpasswd # - sets new account passwords to

Greetings- Running R 2.4.0 under Debian Linux, I am getting a memory error trying to read a very large file: > library(foreign) > oldgrades.df <- read.spss('Individual grades with AI (Nov 7 2006).sav',to.data.frame=TRUE) Error: cannot allocate vector of size 10826 Kb This file is, granted, quite large: aperrin at perrin:/data0/grading$ ls -l total 630304 -r-xr-xr-x 1 aperrin

Greetings- We use smbclient -M to send a Message of the Day to clients every once in a while. The clients are NT4 (SP3), and the server is Samba 1.9.19-prealpha. However, the same problem appears with version 2.0.0. The issue is: once the file to be sent exceeds approximately 675 bytes (smbclient reports sending 975 bytes, presumably including some overhead), the message turns up blank on the

After upgrading to 1.7.0 under debian linux, I can't get e1071 working properly. The first problem I had was that g++-3.0 was the standard compiler but wasn't installed, so I installed it. e1071 then installed correctly, but I get the following: aperrin at perrin:~/afshome/papers/authoritarian/R$ R R : Copyright 2003, The R Development Core Team Version 1.7.0 (2003-04-16) R is free

Greetings- Using R 1.2.2 under linux, I get the following: > l.agg<-xtabs(cbind(r.logic.interests, r.logic.morality, + r.logic.enlightened, r.logic.capacity, r.logic.mediate) + ~ grouptype, + data=gt) Error in parse(file, n, text, prompt) : parse error I know the data are structured fine, as I can use all the elements in individual xtabs()

Returning after the long weekend, I get the following: aperrin at perrin:~/afshome/papers/microcultures/R$ R R : Copyright 2003, The R Development Core Team Version 1.7.0 (2003-04-16) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type `license()' or `licence()' for distribution details. R is a collaborative

Can anyone shed any light on this? > doubt.demographic.pql<-glmmPQL(random = ~ 1 | groupid/participantid, + fixed = r.info.doubt ~ + realage + minority + female + education + income + scenario, + data = fgdata.df[coded.resource,], + na.action=na.omit, +

Recently I've been having this happen frequently: aperrin at perrin:~/microcultures$ R R : Copyright 2002, The R Development Core Team Version 1.5.0 (2002-04-29) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type `license()' or `licence()' for distribution details. R is a collaborative project with many

Sorry if this is obvious, but my S skills aren't great and I haven't been able to find it documented anywhere. I want to write a new function for use with lme objects; the function will simply calculate an ICC (aka "rho") for each level of a mixed-effects model. What I need for this is pretty simple: (c(var1..varn, residual)) / sum(c(var1..varn, residual)) where var1..varn

Greetings- I'm venturing into a new (for me) area of using R: some presentation graphics based on R data. I'd like to compare two distributions of ordinal variables in relatively small (N=203 and 207) subsets of an R dataset. I can get a reasonably good picture of the distributions' differences with: x11() plot(table(hcd.df$auth.sum[hcd.df$datecat==1]),

Greetings- A relatively small request, but here goes. I have some crosstabs, generated with table(), in R: > table(pg.df$grouptype,pg.df$age) 0 1 2 3 4 B 1 3 6 8 3 C 1 3 4 10 7 P 0 2 9 9 8 S 2 9 4 5 16 U 0 15 15 3 0 X 0 0 0 0 0 I would like to export these in latex format using xtable(). But it appears there's no appropriate method for

Greetings- I'm working through Pinheiro and Bates' _Mixed Effects Models in S and S-Plus_ using R (1.3.1 for linux). On page 13 (okay, so I haven't got that far :)) is: plot.design( ergoStool) which returns on my system: > plot.design(ergoStool) Error: couldn't find function "plot.design" any ideas? Thanks.

Please forgive my ignorance on grapics. I'm trying to make a relatively simple plot with two line plots, same axes, by mean over a series of dates. I can make the plot well like this: plot(sort(tapply(first.anti.auth.sum,date,mean), partial=1), type="l", col="yellow",ylim=c(0,2.0)) par(new=TRUE) plot(sort(tapply(first.pro.auth.sum,date,mean), partial=1),