similar to: Generating Interaction Factors (combinations of Data Frame columns)

Hi, i need to create a fractional factorial design sufficient to estimate the main effects. The factors may have any number of levels, let's say any number from 2 to 6. I've tried to use the library conf.design , but i cannot figure out how to write the code. For example, what is the code for a design with 5 factors (2x3x3x5x2) and only main effects not confounded? thanks in advance!

Hi R HELP, I consider the 2^3 factorial experiment described at page 177 of the book Statistics for Experimenters: Design, Innovation, and Discovery by George E. P. Box, J. Stuart Hunter, William G. Hunter (BHH2). This example use the following data in file BHH2-Data/tab0502.dat at ftp://ftp.wiley.com/ in /sci_tech_med/statistics_experimenters/BHH2-Data.zip run T C K y 1 1 -1 -1 -1 60 2

Hi R help, Hi R help, Which is the easiest (most elegant) way to force "aov" to treat numerical variables as categorical ? Sincerely, Andrea Bernasconi DG PROBLEM EXAMPLE I consider the latin squares example described at page 157 of the book: Statistics for Experimenters: Design, Innovation, and Discovery by George E. P. Box, J. Stuart Hunter, William G. Hunter. This example use

Dear R fans, I am preparing a lecture discussing the paper of Wilkinson and APA Task Force on Statistical Inference (1999, American Psychologist, 54, 594-604.) I'd like to demo their Figure 3B (p. 602) with R. That is to add plotMeans(...) with dots of BHH2::dotPlot(...) . Is there any elegant script to do the job? Thanks --------------- LI, Xiaoxu

Dear R experts, Can R make an usual dotplot just like Minitab and other softwares? I have the following data, and can use dotchart to graph a dotplot: y=c(2.873438152e-01, -8.732895642e-01, 4.579001889e-01, 1.047395204e+00, 8.491182299e-02 , -1.938007105e+00, -1.273708343e+00, 9.848010588e-05, 7.238490734e-01, -1.490552717e+00) dotchart(y, xlab="10 observations from

Hi all, I suspect the answer to this query will be the tongue-in-cheek "use a quantum computer", but I thought my understanding might be sufficiently limited that I'm missing a simpler option. I'm looking for a way to cycle through all possible combinations of 2 groups of data. For 10 data points, that's 2^10 combinations, for 20 data points it's 2^20, etc. combn() from

Hello all, I am trying to create a matrix of 1s and -1s without any repetitions for a specified number of columns. e.g. 1s and -1s for 3 columns can be done uniquely in 2^3 ways. -1 -1 -1 -1 -1 1 -1 1 -1 -1 1 1 1 -1 -1 1 -1 1 1 1 -1 1 1 1 and for 4 columns in 2^4 ways and so on. I finally used the function combn([0 1],3) that I found at the following link

It seems people are reinventing the wheel here: The goal is to generate all combinations of 1:n of size k. This (typically) results in a matrix of size k * choose(n,k) i.e. needs O(n ^ k) space, hence is only applicable to relatively small k. Then alternatives have been devised to generate the combinations "one by one", and I think I remember there has been a quiz/challenge about 20

Dear R People: I will be teaching an undergraduate Design of Experiments class in the Spring Semester. It will be very much an applied course. My question, please: has anyone used R for a course like this, please? I've tried Rcmdr for a regression course and just plain command line for a time series course. Should I use Rcmdr, or teach them to use the command line, OR is there something

Hi All Please see the Rprofile file which i have modified as follows and after that when I start R then I see that R says to me "TRUE" for all the packages implying that all loaded at once. But when i try to use commands as simple as help("lm"), it doesnt work nor any of the menu "Packages" is not working. Although the regression using lm ( Y ~ X ) is working

Afternoon everyone, I''ve spent the last week or so looking at all the experimental design packages I can find in R. AlgDesign, design.conf and BHH2 being the best one I could find. Unfortunately none of these do a particularly good job for complex designs, in particular for conjoint or discrete choice. (or perhaps they do, and I can''t make them work correctly)

I can get the interactions between factors like this: > idx=c(1,3,6,9) > jdx=idx > levels(interaction(idx,jdx,lex.order=TRUE)) [1] "1.1" "1.3" "1.6" "1.9" "3.1" "3.3" "3.6" "3.9" "6.1" "6.3" "6.6" "6.9" [13] "9.1" "9.3" "9.6"

Hi, I want draw a dotPlot. All works fine: (Seq <- matrix(c(1, 1, 6, 1, 2, 2, 5, 4, 3, 3, 4, 3, 4, 4, 3, 2, 5, 5, 2, 5, 6, 6, 1, 6), ncol = 6)) dotPlot(Seq[1,], Seq[2,], main = "Sequenz 1 und Sequenz 2", asp = 1) Is there a way to draw a small diagonal, begin at (0/0) to (6/6) (perhaps in red??) or must I use gimp? I have many dotPlots, so it is fine if R can do this. Thanks Joerg

Hi, We were wondering how we could make a stacked frequency diagram such as this one: http://msemac.redwoods.edu/~darnold/math15/liz.pdf We don't necessarily need the shaded "balls", other characters would be fine, such as stacks of x's. David

L.S. We would like to generate fractional design for a conjoint analysis. For example we would like to reduce 2x2x2x2x3 --> 12-16 profiles. We tried the R-package "conjoint" and we found an article which describes how to make fractional design for these kinds of studies with Algdesign: http://tolstoy.newcastle.edu.au/R/e10/help/att-8876/DCE_with_R.pdf However, the generated

Hi All, I've been working on updating the 'genetics' package. As a consequence of the upgrade, .First.lib() looks like: .First.lib <- function(libname, pkgname) { if (!require(combinat)) warning("Unable to load 'combinat' library. Function `diseq.ci' will fail.") require(gregmisc) genotype <-

Dear R-users, I want to know if there is a package that allows to define different experimental designs (factorial, orthogonal, taguchi) and to compare them. I don't found one in the R-web site, but it is possible I missed it! Thank you in advance Sincerely, Marc

Dear developeRs, I encounter the following problem: in the current version of my package FrF2, certain calls to a functioni do not work when package combinat is loaded, because function combn from combinat masks the function from utils that my package uses. I tried to solve this issue by importing function combn into the namespace of FrF2; I don't need to export it, I just want to use it

Dear list, perhpas this question is more suitable for R-dev but since I am not really a developer I post it here first. Apparently the following lines do not create any problem in R: library(combinat) r <- 20; b <- 2; sum( sapply(0:r,function(x) nCm(r,x)^(2*b)) ) > 2^64 while in C I obtain an overflow of data even using unsigned long long and with long double I incurr in precision

Hi I am using R version 2.7.2. on a windows XP OS and have a question concerning an analysis of covariance with count data I am trying to do, I will give details of a scaled down version of the analysis (as I have more covariates and need to take account of over-dispersion etc etc) but as I am sure it is only a simple problem but I just can't see how to fix it. I have a data set with count