search for: optfederov

Hello, we are needing to generate optimal (Fractional) designs for discrete choice applications, where we will be using logistic regression or multinomial logit as the modeling technique. It looks like optFederov, in the AlgDesign package may work, but not sure if this algorithm works when the variable of interest is binary or nominal? Anyone who are experts in this area, anyone interested in consulting with us in this topic (if so, email me we can arrange)? Or can confirm/deny optFederov can work in...

Dear R users, I have used the AlgDesign package to construct a D-optimal exp. design from a file containing a set of allowed runs. The code for the optFederov call is below: #Using optFederov ------------------------------ library(AlgDesign) options(contrasts=c("contr.sum","contr.poly")) file<- read.table("C:/Upstream/Designs/Vodacom Tanzania phase1 grammar/JMP_allowed.txt",sep="\t",header=TRUE,strip.white...

Hi, I have some problems when using AlgDesign->optFederov() generating designs. I have 6 variables, all factors. 3^2 and 4^4, I want to have a design that can take care of main effects and two interactions within 2 pair of variables v3-v4 and v5-v6, the following is the code ################ require(AlgDesign) set.seed(1) levels = c(v1=3,v2=3, v3=4,...

Hi, I am wondering how I should interpreate the output of optFederov() in AlgDesign. Specially I want to know what is $D, $A, $Ge and $Dea, which one I can use as an efficiency to say how good the optimal design is. I only know when a orthogonal design comes, $D = 1. I red the pdf document -- vignette("AlgDesign") [Just type: vignette("AlgDes...

...I can select of course my main effects, but also if I want to see interaction A:B, B:C, A:B:C,but not A:C. This was very interessting as you can end up with fewer runs, especially in cases of 10 factors with 2-3 levels. Is there a way to do this with R? I found the AlgDesign package, and I tried optFederov and optMonteCarlo, as you can set a formula (like: A+B+C+A:B+B:C+A:B:C). But while using this, I end up with to much runs, so I have some residuals. And sometimes I cant get the right interactions from my design. So: are there better ways to achieve the right design? Kind regards Bart [[alterna...

Hi all, Does anybody know if it is possible to build a fractional factorial design in R? That is, suppose that we want do design an experiment with 3 factors with 2, 3 and 3 levels, respectivly. However we want to consider, let's say, only 6 from all possible level combinations. Does R design such experiment? Thanks in advance, Caio [[alternative HTML version deleted]]

Hello R, According to: g <- expand.grid(x = 1:10, y = 5:15, gr = 1:2) g$z <- log((g$x^g$g + g$y^2) * g$gr) wireframe(z ~ x * y, data = g, groups = gr, scales = list(arrows = FALSE), drape = TRUE, colorkey = TRUE, screen = list(z = 30, x = -60)) i have two wireframes in one plot. How could i change the color of the top - one to transparent (or only the grid).

Hi I am trying to generate a design using Algdesign and came across terms of "exact design" and "approxiamte theory design", I did not find a reference to explain what they are, could some one shed some light about this on me? Another question is, I want to measure the main effects and at least two interactions, variables are factors, how do I ensure this in formula,

Hello, I would like to know if there is any function in R which allows to make designs of experiments for Choice-Based Conjoint studies ? I have already checked the topic on " design of experiments with R " and looked at the different libraries. I tried to make my design with the "optFedorov" function but I haven't found how it can allow to have balanced design (with the

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!