similar to: how to generate and evaluate a design using Algdesign

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, 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

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("AlgDesign") in R, you will get

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

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!

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 All, recently I used Design Expert for some Design Of Experiment work. I was happy with the interface to select which effects I want to see in my experiment, and which not. For example: 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

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]]

This practical problem in maximum likelihood estimation must be encountered quite a bit. What do you do when a data point has a probability that comes out in numerical evaluation to zero? In calculating the log likelihood you then have a log(0) problem. Here is a simple example (probit) which illustrates the problem: x<-c(1,2,3,4,100) ntrials<-100 yes<-round(ntrials*pnorm((x-3)/1))

Hi all, I have a problem in including my plot in a loop. Here is a simple example for one plot: # Plot simple graph with super- and subscript a<-c(1,2,3,4) b<-c(1,2,3,4) plot(x=a,y=b, ylab=expression(paste("Apple"["P"])), xlab=expression(paste("Banana"^"th")),

Dear r-helpers, Could you please help me solve the following problem: When I run require(AlgDesign) trt <- LETTERS[1:5] blk <- 10 trtblk <- 3 BIB <- optBlock(~., withinData = trt, blocksizes = rep(trtblk, blk)) In response to the last command, R complains: Error in optBlock(~., withinData = trt, blocksizes = rep(trtblk, blk)) : object ".Random.seed" not found The

Dear DevelopeRs, in continuing with my suite of packages on experimental design, I am stuck with an issue that appears to be related to package AlgDesign - I have tried to get it solved by Bob Wheeler, but he seems to be stuck as well. Whenever AlgDesign is loaded, some of my code does not work any more. For example, in a fresh R session: require(DoE.base) fac.design(nlevels=c(2,6,2))

I can not understand why this fails > > faicoutput2 <- list(stuff21 = as.numeric(faicout$coefficients[2]), + stuff31=as.numeric(faicout$coefficients[3]), + stuff41=as.numeric(faicout$coefficients[4]), + stuff32=(stuff21-stuff31), + stuff42=(stuff21-stuff41), +

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

I have two data frame A and B adn want to cross them. A has format as: a1 a2 a3 1 2 3 2 3 1 1 3 2 ... B: b1 b2 1 2 2 1 ... the combine result shall be something like a1 a2 a3 b1 b2 1 2 3 1 2 1 2 3 2 1 2 3 1 1 2 2 3 1 2 1 1 3 2 1 2 1 3 2 2 1 .... is there a function able of doing this instead of loops? Thanks, Sun

R CMD check on a Windows system, halts with the following; installing inst files FIND: Parameter format not correct make[2]: *** [C:/AlgDesign/AlgDesign.Rcheck/AlgDesign/inst]Error 2 make[1] *** [all] Error 2 make: *** [pkg-AlgDesign] Error2 *** Installation of AlgDesign failed **** The inst directory contains the sub directory doc with a pdf and dvi file. Any sub directory in inst seems to

AlgDesign is a new package for calculating algorithmic experimental designs. It will calculate both exact and approximate designs for a variety of criteria. It will handle very large designs. It will also block designs in a variety of ways, including split plotting. You should find it at least as capable as other software for this purpose. I'd normally submit this sort of thing to beta test,

AlgDesign is a new package for calculating algorithmic experimental designs. It will calculate both exact and approximate designs for a variety of criteria. It will handle very large designs. It will also block designs in a variety of ways, including split plotting. You should find it at least as capable as other software for this purpose. I'd normally submit this sort of thing to beta test,

Can anyone explain why AlgDesign's expand.formula help and output differ? #From help: # quad(A,B,C) makes ~(A+B+C)^2+I(A^2)+I(B^2)+I(C^2) expand.formula(~quad(A+B+C)) #actually gives ~(A + B + C)^2 + I(A + B + C^2) They don't _look_ the same... Steve E ******************************************************************* This email contains information which may be confidential and/or

hi there!! i am trying to implement the code of the e1071 package for naive bayes, but it doens't really work, any ideas?? i am very glad about any help!! i need a naive bayes with 10-fold cross validation: code: library(e1071) model <- naiveBayes(code ~ ., mydata) tune.control <- tune.control(random = FALSE, nrepeat = 1, repeat.aggregate = min, sampling = c("cross"),