similar to: AlgDesign--exact and approximate design

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,v4=4,v5=4,v6=4)

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-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))

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).

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")),

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

Dear R community, I would like to compare the degree of aggregation (or dispersion) of bacteria isolated from plant material. My data are discrete counts from leaf washes. While I do have xy coordinates for each plant, it is aggregation in the sense of the concentration of bacteria in high density patches that I am interested in. My attempt to analyze this was to fit negative binomial

Dear all, I would like to Boostrap the stepAIC() procedure from package MASS for variety of model objects, i.e., fn <- function(object, data, B = 2){ n <- nrow(data) res <- vector(mode = "list", length = B) index <- sample(n, n * B, replace = TRUE) dim(index) <- c(n, B) for (i in 1:B) { up.obj <- update(object, data = data[index[, i], ])

Dear developeRs, I have not found anything recent about how to link to a vignette or other documentation from within Rd-files. Is this now possible with the new help system ? For example, I would like to link to the file AlgDesign.pdf provided within the doc directory of package AlgDesign. Thanks for any suggestions, regards, Ulrike -- View this message in context:

Hi, I am trying to convert a variable a = sample(1:3,100,rep = T) represents choices into a 3X100 dummy varible b with corresponding element set to 1 otherwise 0. eg. a: 1 3 2 1 2 3 1 1.... b: 1 0 0 1 0 0 1 1.. 0 0 1 0 1 0 0 0... 0 1 0 0 0 1 0 0... Is there something like b[a] =1 existing? I could not figure this out myself. ---------------------------------

Hi, I have a data frame df with column names a,b and c. Now I want to get a subset of df that satified the condition a == 1 and b == 2, how do I specify this. For one condition like a == 1 I can use subdf = df[,df$a==1] to get the right answer, but subdf = df[,df$a==1 && df$b ==2] does not return the right answer. Some quick tips please.

predict.lm has been broken by recent changes to the patched branch. It fails for all singular fits. An example: library(MASS) data(quine) quine.hi <- aov(log(Days + 2.5) ~ .^4, quine) quine.nxt <- update(quine.hi, . ~ . - Eth:Sex:Age:Lrn) predict(quine.nxt) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 NA NA NA NA NA NA NA NA NA NA NA NA NA