similar to: latex tables for 3+ dimensional tables/arrays

Suppose I have a table constructed from structable or simply just an object of class table. How can I convert it to a latex object? I looked in RSiteSearch, but only found info about matrices or data frames. Steve For example, here is a table t2 > str(t2) table [1:2, 1:2, 1:2] 6 8 594 592 57 ... - attr(*, "dimnames")=List of 3 ..$ Hospital : chr [1:2] "A"

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

aperm() was designed for multidimensional arrays, but is also useful for table objects, particularly with the lattice, vcd and vcdExtra packages. But aperm() was designed and implemented before other related object classes were conceived, and I propose a small tune-up to make it more generally useful. The problem is that aperm() always returns an object of class 'array', which

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",

Hallo I encountered a behaviour which puzzles me (but finally I did get what I wanted). I used structable and strucplot but I wanted to change names of variables in structable object. I tried to subset it, use names but to no avail. So I tried str and expected to get a structure of an object but: > sss<-structable(Titanic) > str(sss) Error in "[.structable"(x, args[[1]],

Hi everyone, I am trying to build a table putting standard errors horizontally. I haven't been able to do it. library(memisc) berkeley <- aggregate(Table(Admit,Freq)~.,data=UCBAdmissions) berk0 <- glm(cbind(Admitted,Rejected)~1,data=berkeley,family="binomial") berk1 <- glm(cbind(Admitted,Rejected)~Gender,data=berkeley,family="binomial") berk2 <-

Hi everyone, I am trying to build a table putting standard errors horizontally. I haven't been able to do it. library(memisc) berkeley <- aggregate(Table(Admit,Freq)~.,data=UCBAdmissions) berk0 <- glm(cbind(Admitted,Rejected)~1,data=berkeley,family="binomial") berk1 <- glm(cbind(Admitted,Rejected)~Gender,data=berkeley,family="binomial") berk2 <-

Frank Harrell rote in a message dating from Oct 8th: > n.group is an argument to latex.default in the Hmisc package I must admit that I can't find it in the function head, which reads on my installation: function (object, title = first.word(deparse(substitute(object))), file = paste(title, ".tex", sep = ""), append = FALSE, label = title, rowlabel = title,

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

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)

> 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

> On May 23, 2016, at 11:46 AM, Ernest Adrogu? <eac at openmailbox.org> wrote: > > Hello, > > Currently it's possible to convert an object of class table to a data frame > with as.data.frame.table(), but there's no ready-made function, AFAIK, to do > the reverse operation, i.e. conversion of a data frame to a table. > > Do you think it would be a good

Hello, Currently it's possible to convert an object of class table to a data frame with as.data.frame.table(), but there's no ready-made function, AFAIK, to do the reverse operation, i.e. conversion of a data frame to a table. Do you think it would be a good idea to add a data.frame method to as.table(), to allow such conversions? The idea is that if `x' is a table and `y <-

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

I'm running Samba 2.0.3 from the pre-built binary (ftp://sunsite.org.uk/packages/samba/Binary_Packages/solaris/samba-2.0.3 -sunos-4.1.3.tar.Z) on a Sun IPX with SunOS 4.1.3_U1. I've defined a printer in smb.conf, from a PC (NT 4.0) I can send prints to it and view the queue OK but I can't manage the queue in any way. Attempts to cancel prints and stop or start the queue from the PC

Hello. I'm trying to find a way in R to calculate between and within subject variances and confidence intervals for some analytical method development data. I've found a reference to a method in Burdick, R. K. & Graybill, F. A. 1992, Confidence Intervals on variance components, CRC Press. This example is for Balanced Data confidence interval calculation from Pg 62. The data are

Hi, Just tested the latest snapshot on RHL72 via building RPM's of it. Nroff detection was wrong, and if no --with-mantype was specified, the type would always revert to cat. This one-byter fixes it. -- Pekka Savola "Tell me of difficulties surmounted, Netcore Oy not those you stumble over and fall" Systems. Networks. Security. -- Robert

Hi, I have the following problem (library Hmisc loaded, iris data loaded, R Version 1.7.0 (2003-04-16), packages updated, running on a linux Debian i386): > summary(Species~Sepal.Length,method="reverse")->a > a Descriptive Statistics by Species +------------+-----------------+-----------------+-----------------+ | |setosa |versicolor |virginica

Dear all, an hopefully quick table question. I have the following data: Two objects that are 2*9 matrix with nine column names (Dis1, ..., Dis9) and the row names (2010,2020). The content are frequencies (numeric). In want to create a table that is along the lines of ftable(UCBAdmissions) and should looks like this: Dis1 | ...| Dis9 2010|2020|....|2010|2020 (first row,first column is the value