similar to: library vcd for R rw2001

'barplot' doesn't seem to work with vcd library. Am I supposed to detach vcd when I want to use barplot? Here's an example. Say I have the following matrix, > m <- matrix(c(1,2,3, 4,5,6, 3,4,5, 2,3,4), ncol=4) > m [,1] [,2] [,3] [,4] [1,] 1 4 3 2 [2,] 2 5 4 3 [3,] 3 6 5 4 Then > barplot(m) gives a barplot of the data. However,

Dear all, I have a problem to make figures with two columns in package vcd. Here an example code I take from "\library\vcd\html\plot.loglm.html" What I need, I want to make two figures in one plot. How could I do that. I have tried with layout(rbind(c(1, 1, 2, 2))) but the same result, two plot. Best wishes, Muhammad Subianto library(vcd) oldpar <- par(mfrow=c(1, 2)) ## mosaic

Hello, I'm trying to use the vcd package to analyze survey data. Expert judges ranked possible features for product packaging. Seven features were listed, and 19 judges split between 2 cities ranked them. The following code (1) works, but the side-by-side plots for Cities PX, SF are shrunk too much. Stacking PX on top of SF would make for a better plot. (I could switch the order of

require(vcd) mosaic(matrix(1:6, 2, 3), gp=gpar(fill=c("red","gray","blue")), main="three colors in each row") mosaic(matrix(1:3, 1, 3), gp=gpar(fill=c("red","gray","blue")), main="only one color in each row") I anticipated three colors in the second plot. My guess is that there is a matrix subscript without

********************************************************************** This email and any files transmitted with it are confidential and intended solely for the use of the individual or entity to whom they are addressed. If you have received this email in error please notify the system manager. ********************************************************************** Hi Just installing R and some

Hello, I am trying to use the extended assocplot() function: assoc(), from vcd package. Trouble is that it cannot even run its own examples on my installation. I get this output: $> example(assoc) assoc> data("HairEyeColor") assoc> (x <- margin.table(HairEyeColor, c(1, 2))) Eye Hair Brown Blue Hazel Green Black 68 20 15 5 Brown 119 84 54

Sorry, sorry.... of course levels(testf)[c(2,1,3)] will do the job My excuses to all Anne PS I will meditate the following saying "la parole est d'argent et le silence est d'or" BONNES FETES A TOUS SEASONAL GREETINGS ---------------------------------------------------- Anne Piotet Tel: +41 79 359 83 32 (mobile) Email: anne.piotet@m-td.com

Hello R helpers! I looked but did not find a table-lookup R-utility. I could use a loop to do the job (old FORTRAN/C habits die hard) but if I have a big table in which I have to search for the values corresponding to a vector, I end up logically with a double loop. Is there already such a utility? Otherwise, is there a way without loops? Thanks as always Anne

I have troubles understanding how goodfit() function in the vcd package computes the Pearson coefficient. Can anybody provide more information on the computation? In particular, for HorseKicks data in vcd package, goodfit() yields > oo <- goodfit(HorseKicks,type="poisson",method="MinChisq") > summary(oo) Goodness-of-fit test for poisson distribution

Hello: What is the most efficient way to change the plotted variable names in mosaic plots in the vcd package? Should one do a separate contingency table first, change the dimension names there and then pass that to mosaic? Or is there a way to do it simply within mosaic. I was thinking something like: mosaic(~var1+var2, labelling_args=list(varnames=c('newvar1', 'newvar2')) Simon

Hello! I would like to know if there is a simple way to reorder levels of a given factor.Let's say that the vector testf<-factor(c("red","red","red","blue","blue","white")) levels(testf) : blue red white should have reordered levels such as levels(testf) : red blue white (this is for presentation purposes) I guess

I need to plot multiple sets of data, on one Ternary plot (from the VCD package). Since they all need to be formatted differently, I can't just coerce them into one matrix, I need three separate calls. Is there a way to do this? Thanks -- View this message in context: http://www.nabble.com/Plot-multiple-datasets-on-a-VCD-ternary-graph-tp18412092p18412092.html Sent from the R help mailing

Hello, I am looking for a way to convert VCD tracks to theora. I'd rather a command line tool. What would you suggest me? I already found I can do that with mplayer, by ripping to yuv and wav, then using the encoder_example to compress to theora, but would there be another better way? -- ASPO Infog?rance http://aspo.rktmb.org/activites/infogerance Unofficial FAQ fcolc

Hi, I'm trying to get 2x2 (or other layouts) of cd_plot from the vcd package. I have tried the usual commands like layout, par(mfrow...) etc and but cd_plot seems to ignore them and send the plotting window back to 1x1. I have also tried turning off the pop and newpage options in cd_plot but I still can't get multiple cd_plots into a plotting window. Any suggestions would be greatly

Hi, I like mosaic function of "vcd" package. I have played around it. I have found out that mosaic plot data table is 2-dimension does not stretch when you enlarge a mosaic plot. It is okay when data table is 3 or more dimension. The first one is of 3-dimension table case, and the second one is 2-dimension. With the first plot, you can drag window to enlarge a plot. With the

Hi! Is there an easy way to add to the scree-plot labels to each value pertaining to the cumulative proportion of explained variance? Thanks and a happy new year Anne ---------------------------------------------------- Anne Piotet Tel: +41 79 359 83 32 (mobile) Email: anne.piotet@m-td.com --------------------------------------------------- M-TD Modelling and Technology Development PSE-C

Hi! I'm trying to do some ploytomous logistic regression using multinom() in the nnet package, but am a bit confused about interpretation of the results Is it possible to get the following quantities: I: maximum likelihood estimates to test for fit of model and significance of each predictor (I would like to produce a table of the following type) Analysis of Variance: MLE (values are

hello to all! I have a small problem wit predict() for lm Let's say I have predictors x1 and x2, response y I want to predict for a new ds say dn<-data.frame(x1= seq(min(x1),max(x1),length=10),x2=rep(median(x2),10)) predict(lm(y~x1+x2),dn,se.fit=T) Error message > Error: variables 'x1', 'x2' were specified differently from the fit (I looked in the help and found

Dear R-helpers, I have a problem which I suppose is trivila, but... I have included NA values as factors ( (to be able to make nice printed summaries with NAs % ba category ) with the following code dat$x.f<-factor(dat$x, exclude=NULL); levels(dat$x.f)<-c("A1","A2","A3","A4","NA"); length(dat$x.f) Now, I want to impute the missing values.

Hello R helpers! I'm using the avas function form package acepack (called from areg.boot package Hmisc) to estimate automatically transformations of predictors (in this case monotonous) and response. Well, it seems to work quite well, but I have 3 basic questions: - which set of basis functions is used in this procedure? - how do I back transform my estimate (y hat ) to the originasl scale?