similar to: aperm() should retain class of input object

I'm looking for an R method to produce latex versions of tables for table/array objects of 3 or more dimensions, which, of necessity is flattened to a 2D display, for example with ftable(), or vcd::structable, as shown below. I'd be happy to settle for a flexible solution for the 3D case. > UCB <- aperm(UCBAdmissions, c(2, 1, 3)) > ftable(UCB) Dept A B

Dear List, I'm having problem with an exercise from The R book (M.J. Crawley) on page 567. Here is the entire code upto the point where I get an error. data(UCBAdmissions) x <- aperm(UCBAdmissions, c(2, 1, 3)) names(dimnames(x)) <- c("Sex", "Admit?", "Department") ftable(x) fourfoldplot(x, margin = 2) dept<-gl(6,4) sex<-gl(2,1,24)

R version 1.0.1 OS RedHat Linux 6.1 In attempting to test for numeric vectors in a data frame, I tried: apply(dataframe,2,is.numeric) and found that it returned FALSE for all vectors whether they were numeric or not. I tracked this to the fact that as.array() was converting the data frame to character vectors, and thought I could solve it by using array(), which preserved the mode of the

I think that the "dimname names" of tables and arrays could make aperm() and apply() (and probably some other functions) easier to use. (dimname names are, for example, created by table() ) The use would be something like: -- x <-table( from=sample(3,100,rep=T), to=sample(5,100,rep=T)) trans <- x / apply(x,"from",sum) y <- aperm( trans,

Hi everyone. I'm playing with aperm(): a <- 1:24 dim(a) <- c(2,3,2,2) permutation <- c(1,2,4,3) b <- aperm(a,permutation) So if my understanding is right, a[1,3,2,1] == b[c(1,3,2,1)[permutation] ] but this isn't what I want because the RHS evaluates to a vector, and I am trying to identify a single element of b. How do I modify the RHS to give what I want? Following

Following some discussion on R-help, I'd like to propose that an as.matrix method be added to those available for ftable objects. The reason for this is that there are a variety of situations where one needs to flatten a 3+ way table, but then use that for analysis as a matrix, not just for pretty-printing. There is an as.table method to turn the result back to a table, but an as.matrix

I apologize in advance if this is the wrong forum for this report/request, and for the fact that I have not read the code for ftable.formula in any detail. >From reading the documentation for ftable.formula, I expected that the following two calls to ftable would produce the same results: data(UCBAdmissions) ftable(UCBAdmissions, row.vars = "Dept", col.vars = c("Gender",

Hi, I have noticed that aperm is very slow, and I wondered if there was a way of speeding it up. Let me tell you a bit about the context of my problem, because perhaps I shouldn't be using aperm at all. The context is probabilistic inference in graphical models. One of the most fundamental operations is two compute an element-wise multiplication of two arrays of different sizes, say A and B.

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

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

> addmargins(UCBAdmissions, FUN = list(Total=sum)) works with no problems, but consider: > myFUN <- list(Total=sum) > addmargins(UCBAdmissions, FUN = myFUN) Error in "names<-.default"(`*tmp*`, value = "") : names() applied to a non-vector Is this a bug? > R.version _ platform i386-pc-mingw32 arch i386 os mingw32 system

Just a general question concerning the woolf test (package vcd), when we have stratified data (2x2 tables) and when the p.value of the woolf-test is below 0.05 then we assume that there is a heterogeneity and a common odds ratio cannot be computed? Does this mean that we have to try to add more stratification variables (stratify more) to make the woolf-test p.value insignificant? Also in the

Hello: I've found structures like "normal-bracket50bracket-normal" in help files for R packages including the following: * "mergeprepare" and "mergematrices" in a document dated March 3, 2004 by Richard Mott; the second contains "normal-bracket30bracket-normal". * "Fperm.fd" and "tperm.fd" in the

I have been tinkering with mosaicplot() and friends as a way of learning R. As part of this, I've written a pair.table() method for mosaic matrices, and would like to extend mosaicplot to work with loglin and logln (MASS) objects. I'm using R 1.4.0 on Win 98. I've been trying to figure out the formula interface, and think there's a bug, but not sure how to find it, yet alone fix

Sure -- thanks -- only took me 3-4 attempts to get aperm to work (as opposed to really thinking hard about how it works ;-) On 9/28/2017 11:55 AM, Duncan Murdoch wrote: > On 28/09/2017 9:10 AM, Evan Cooch wrote: >> Thanks for both the mapply and array approaches! However, although >> intended to generate the same result, they don't: >> >> # mapply approach

Muchas gracias Javier, Lo que yo quiero es cambiar el título de la leyenda que dice "Pearson residuals" a español "Residuales de Pearson", pero no me doy cuenta como. También en lugar de "p-value", que diga "Valor de P". Es posible? Manuel 2013/7/4 Marcuzzi, Javier Rubén <javier.ruben.marcuzzi@gmail.com> > Estimado Manuel Spíndola > >

Dear all, I have been working on an idempotent version of apply, such that applying a function f(x) = x (ie. force) returns the same array (or a permutation of it depending on the order of the margins): a <- array(1:27, c(2,3,4)) all.equal(a, iapply(a, 1, force)) all.equal(a, iapply(a, 1:2, force)) all.equal(a, iapply(a, 1:3, force)) all.equal(aperm(a, c(2,1,3)), iapply(a, 2, force))

The use of aperm is unnecessary if you call array() properly. ms <- array(c(rep(0, 5),so,sa*m,sa), c(5, 2, 2)) -- Sent from my phone. Please excuse my brevity. On September 28, 2017 9:10:26 AM PDT, Evan Cooch <evan.cooch at gmail.com> wrote: >Sure -- thanks -- only took me 3-4 attempts to get aperm to work (as >opposed to really thinking hard about how it works ;-) > >On

I need to change the font(s) used in mosaic from package vcd. The help file and the vignette do not give very explicit examples for doing that. The easiest solution would be changing the font for everything on the graph: var labels, var names, title, subtitle, and cell labels. What is the easiest way of accomplishing this?

Hi all, Could somebody be so kind to explain to me what is the saturated model on which deviance and degrees of freedom are calculated when fitting a binomial glm? Everything makes sense if I fit the model using as response a vector of proportions or a two-column matrix. But when the response is a factor and counts are specified via the "weights" argument, I am kind of lost as far as