similar to: Memory error

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, 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):

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

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

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 - is there any update on a PostgreSQL driver for the DBI package? If not, what's the currently-preferred method of creating a link from a PostgreSQL database and R? Thanks. ---------------------------------------------------------------------- Andrew J Perrin - andrew_perrin (at) unc.edu - http://www.unc.edu/~aperrin Assistant Professor of Sociology; Book Review Editor, _Social

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, +

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- I have some data on which I need to do something like a Hierarchical Linear Model (please bear with me, I'm only learning the technique so I don't know yet if my language is correct). Essentially I'm analyzing data at two levels simultaneously; data are about individuals an organizations of which they are members. Can someone point me toward an appropriate package in R?

Greetings- An odd situation has developed. I use the following code to create .eps files of two very similar graphs: postscript(file='resources.bygt.eps', onefile=FALSE, horizontal=TRUE) barplot(resources.bygt.matrix, beside = TRUE, legend.text=c('narrative','doubt'),

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()

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),

Greetings- I have a strange problem displaying a graph from R (1.3.1, linux) in a LaTeX document of documentclass seminar. I'm using graphicx to include the file: \usepackage{graphicx} ... \resizebox{\textwidth}{\textheight}{\includegraphics{crime.eps}} When I do this, the entire slide (including the page number) is rotated 180 degrees. Any ideas why this happens? The graph was created

I'd like to produce a series of simple line graphs for my methods class that show the three questions used on a repeated survey to make up a particular index. The data frame is: > efficacy.df year complicated havesay dontcare 1 1952 71 68 63 2 1954 NA NA NA 3 1956 64 71 71 4 1958 NA NA NA 5 1960

Greetings. I've been experimenting with some algorithms for document classification (specifically, a Naive Bayes classifier and a kNN classifier) and I would now like to calculate some inter-rater reliability scores. I have the data in a PostgreSQL database, such that for each document, each measure (there are 9) has three variables: ap_(measure), nb_(measure), and knn_(measure). ap is me

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

Any ideas on this? nujoma:~> R R : Copyright 2002, The R Development Core Team Version 1.5.0 (2002-04-29) ... Error: couldn't find function ".Alias" Error: couldn't find function "attach" [Previously saved workspace restored] > q() Error: couldn't find function "q" > Suspended nujoma:~> kill %1 This is on a brand-new installation of R