similar to: how to make automatically each level from data.frame to vector

The data is in the attachment. What I wanna get is: , , Sex = Male Eye Hair Brown Blue Hazel Green Black 32 11 10 3 Brown 53 50 25 15 Red 10 10 7 7 Blond 3 30 5 8 , , Sex = Female Eye Hair Brown Blue Hazel Green Black 36 9 5 2 Brown 66 34 29 14 Red 16 7 7 7 Blond 4

I'm looking for a way to generalize the calculation of (log) odds ratios for 2 x 2 x {strata} frequency tables in vcd::oddsratio() to R x C x {strata} tables. For an R x C table, F, odds ratios can be defined in several ways; one simple way, particularly for tables with ordered factors, is to calculate the set of continuation odds ratios, based on the (R-1)x(C-1) set of 2x2 tables with

My question is based on an example provided in the following: Referencing: Statistics with R Vincent Zoonekynd <zoonek at math.jussieu.fr> 6th January 2007 URL: http://zoonek2.free.fr/UNIX/48_R/all.html data(HairEyeColor) a <- as.table( apply(HairEyeColor, c(1,2), sum) ) # Provided Example barplot(a, beside = TRUE, legend.text = attr(a, "dimnames")$Hair) # I

I have an application where I have a function to calculate results for a 2-way table or matrix, which returns a matrix with one less row and column. To keep this short, the function below captures the structure: fun2way <- function(f){ if (!length(dim(f)) ==2) stop("only for 2-way arrays") R <- dim(f)[1] C <- dim(f)[2] f[1:(R-1), 1:(C-1)] } Now, I want to

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

It appears that HSAURtable only works on two dimensional tables. Is this correct? For example, here is HairEyeColor: , , Sex = Male Eye Hair Brown Blue Hazel Green Black 32 11 10 3 Brown 38 50 25 15 Red 10 10 7 7 Blond 3 30 5 8 , , Sex = Female Eye Hair Brown Blue Hazel Green Black 36 9 5 2

Hi, I would like to do a multiple correspondence analysis with the mca function in the MASS library on data that I have as a contingency table (which I've tried converting to a data frame). For example, ========= > data(HairEyeColor) > hair.df <- as.data.frame(HairEyeColor) > hair.df Hair Eye Sex Freq 1 Black Brown Male 32 2 Brown Brown Male 38 3 Red

Suppose I have an n-diml array A and I want to extract the first "row" -- ie all elements A[1, ...] Interactively if I know 'n' I can write A[1,,,,,] with (n-1) commas. How do I do the same more generally, eg in a script? (I can think of doing this by converting A to a vector then extracting the approp elements then reshaping it to an array, but I wonder if there isn't a

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

I am using R to teach, and here are a couple of things that I thought would work didn't work. 1. I noticed the utility data(***,package=***) recently and like it very much, but unless I type in the whole word "package" I'll get an error in 1.4.0. For example, data(cats,package=MASS) works fine but data(cats,pac=MASS) doesn't. 2. drop1 doesn't seem to be as smart as

Dear R users, I have a problem, which I can not find a solution. Probably someone could help me? I have a result from my classification, like this > credit.toy [[1]] age married ownhouse income gender class 1 20-30 no no low male good 2 40-50 no yes medium female good [[2]] age married ownhouse income gender class 1 20-30 yes yes high male

I've just started learning R, so I'm still on the steep part of the learning curve, but my enthusiasm was heightened by learning that there's a very nice implementation of mosaicplot(). As a learning project, I've already done a basic implementation of a pairs.table() function which does a mosaic scatterplot matrix, and now I'm trying to do conditional mosaic plots (discrete

It being friday, I would like to call your attention to an innovative data analysis by Leslie Lamport available from: http://research.microsoft.com/users/lamport/pubs/hair.pdf I particularly liked the graphics. url: www.econ.uiuc.edu/~roger Roger Koenker email rkoenker at uiuc.edu Department of Economics vox: 217-333-4558 University of Illinois

Dear R users, I am using v2.0.1 on Windows 2000. I have read a ".dat" file with several vectors, including 2 factors (2 levels x 3 levels), and a vector of responses, into R. There are no unique row names. When I try plot(x,y) or lm(y~x) the following error is returned: Error in model.frame(formula, rownames,...extranames: variable lengths differ What am I doing wrong? I am a

Dear everybody: We used the fine foreign library to bring in an SPSS dataset that was about 9 megabytes and I can squeeze it into a much smaller R object using compression with save(ndat, file="NatAnnES2000.rda", compress=T). I can use load() to get the "ndat" dataframe back, that's all good as far as I can see. If I put that file in the data subdirectory, then the

Reading "R Internals" made me believe that R_UnboundValue was a placeholder that would be skipped over in variable lookup. viz. the section of R Internals "Hash tables" says "items are not actually deleted but have their value set to R_UnboundValue.", which seems to align with what I read in envir.c. So, I reasoned, if I have a function that returns R_UnboundValue,

Hi All, I have the data like this : >sample <- read.csv(file="sample.csv",sep=",",header=TRUE) > sample stdate Domain sex age Login 1 01/11/09 xxx FeMale 25 2 2 01/11/09 xxx FeMale 35 4 3 01/11/09 xxx Male 18 30 4 01/11/09 xxx Male 31 3 5 02/11/09 xxx Male 32 11 6 02/11/09 xxx Male 31 1 7 02/11/09

Dear list, I have following data set, which I want to plot the "Scale" variable on the x-axis and "Mean"´on the y-axis for each Ageclass and for each sex. The Mean value of each Ageclass for each sex would be connected by a line. Totally, there should be 6 lines, from which three present the Mean values of each Ageclass for respective sex. Are there any easy ways to do

Hello R-users/experts, I am new to R- I have a simple question: Let say I have a data set as follows temp:[file attached] the data structure is a follows: sex age female 28 female 53 female 53 female 36 male 42 male 29 male 43 male 36 male 41 Here we are grouping all male value into male and all female value in to female

I'm trying to remove the elements "No" from the character vector