similar to: Re : Custom axis

Yes, you're right. In fact, it's just an adaptation of a matlab command and the author advises using N^4 replications that's why it's the default in the function. The bistochastic matrix is not my subject of interest, but I need it to perform some random tranformation of a vector of incomes. Florent Bresson ----- Message d'origine ---- De : Richard M. Heiberger <rmh at

Thanks, I tried someting like this, but computation takes times for large matrices btransf <- function(y,X=length(y)^4) { N <- length(y) bm <- matrix(rep(1/N,N^2),N,N) for(j in 1:X){ coord <- sample(1:N,4,replace=T) d <- runif(1,0,min(bm[coord[1],coord[2]],bm[coord[3],coord[4]]))

Please, I would like to generate a random bistochastic matrix, that is a squared matrix of non-negative numbers with each row and each column sum to 1, for example : .2 .3 .5 .6 .3 .1 .2 .4 .4 I don't know of to code this. Do you have any idea ? Thanks Florent Bresson ___________________________________________________________________________ Demandez ?

Dear all, I try to run the example of lmer and get the following error message. > library(lme4) > example(lmer) lmer> (fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy)) [[1]] Error in get(x, envir, mode, inherits) : variable "as.dpoMatrix" was not found This error message is similar to what I get with other models. It looks like the mer class has a slightly

I have to estimate the following model for several group of observations : y(1-y) = p[1]*(x^2-y) + p[2]*y*(x-1) + p[3]*(x-y) with constraints : p[1]+p[3] >= 1 p[1]+p[2]+p[3]+1 >= 0 p[3] >= 0 I use the following code : func <- sum((y(1-y) - p[1]*(x^2-y) + p[2]*y*(x-1) + p[3]*(x-y))^2) estim <- optim( c(1,0,0),func, method="L-BFGS-B" , lower=c(1-p[3], -p[1]-p[3]-1,

Hi, I'm using the density() command for a given vector x and I would like to know how to get the estimated value of the density for each element of the vector x instead of values corresponding to points from a grid. Thanks Florent Bresson

Dear R-users, I would like to apply a function (more precisely sd()) over the third dimension of a three-dimension array. The function apply would be interesting but the chosen function can only be applied on the rows and columns of the array according to the help file. I can use a loop to cut the array in matrices and then use apply for each replication, but it's not very nice. A small

I have to calculate some formula like: gamma(x)/(gamma(x+y) and I observed that for relatively big values of x, R returns infinity and so cannot compute the formula. Is it possible to force R to give the real value of gamma(x) instead of Inf ? thanks

I have defined a function to compute the value of a beta distribution of the second kind (the existing beta distribution of th stats package is the beta distribution of the first kind). It works perfectly for a single value, but I want to apply it to a vector of 22 000 values. I can use a loop for the calculation of each value but it runs very very slowly. So, what can I change ? Hers's the

I' m trying to compute weighted mean on different groups but it only returns NA. If I use the following data.frame truc: x y w 1 1 1 1 2 2 1 3 1 1 4 2 0 2 1 0 3 2 0 4 1 0 5 1 where x is a factor, and then use the command : tapply(truc$y,list(truc$x),wtd.mean, weights=truc$w) I just get NA. What's the problem ? What can I do ?

Dear R-users, I'm facing a problem with the import of data in R. I have a sav file that, I presume, uses some Arabic encoding (but I don't know which one) and I would like to read it with R. When I use the function read.spss (I also tried spss.get(Hmisc)), I get the following message: > read.spss("Hhld.sav") Erreur dans read.spss("Hhld.sav") : erreur ? la lecture

I'm trying to run a nls on a subset of a data.frame. In the subset, one observation is NA. So I drop the observation but when I ask for : >sm <- nls(machin$revcum ~ Lc.singh(machin$popcum,p), start=list(p=c(2,3))) I get : Erreur dans parse(file, n, text, prompt) : syntax error in "~ " If I put some value for the non available observation instead of droping it, it works.

Hi, I have to use a loop to perform a quite computer intensive estimation and I would like to know the progress of the loop during the process. I tried to include something like print(paste(k,date(),sep=" : ")) where k is the number of the iteration, but the result appears only at the end of the loop. Can someone help me please ?

I have to compute some standard errors using the delta method and so have to use the command "numericDeriv" to get the desired gradient. Befor using it on my complicated function, I've done a try with a simple exemple : x <- 1:5 numericDeriv(quote(x^2),"x") and i get : [1] 1 8 27 64 125 216 attr(,"gradient") [,1] [,2] [,3] [,4] [,5] [,6] [1,] Inf

Hi, I have a lattice xyplot that contains panels according to FactorA, and curves for the 2 levels of Factor B within a panel. I try to add text in the panels of a lattice graph. I suppose I have to write a custom function (panel.txt). What I really would like is to adapt the text in the panel according to the levels of FactorA. In the manuals, I find examples for the strips using which.given

Could anybody explain this difference in the function order() between R under windows and R under Linux ? It seems that under Linux the order in of character dsitinguishes between caps and normal letters and sorts them starting with the capitals (see below). How can I avoid this (I mean: get the same results as I get under Windows)? Thanks Joris Under Windows R 1.6.2 > mstring <-

Hi, I' trying to learn how to use lme for Linear Mixed Models and I have a problem when I have to include more than one random effect in my model. I know that this could be a stupid question to ask, but I'm not able to solve it by myself... One example: if my model is response = operator + block + day with operator and block as fixed effects and day as random effect, I use res.lme

Hi, I've got a very simple problem but cannot find the solution. I'm using two data frames (say X and Y) and I want to get a subset of one according to the different levels of a variable "code" of the other data frame. I tried something like Z <- subset(X, code==levels(Y$code)) (1) but it does not work. I do not want to do something like Z <-

Dear members, I would like to switch from nlme to lme4 and try to translate some of my models that worked fine with lme. I have problems with the pdMat classes. Below a toy dataset with a fixed effect F and a random effect R. I gave also 2 similar lme models. The one containing pdLogChol (lme1) is easy to translate (as it is an explicit notation of the default model) The more parsimonious

I have succeded in defining the cdf of the generalized beta of the second kind, eg. pgbeta2 <- function(quint,b,a,p1,p2) { integrate(function(x) {exp(log(a)+(a*p1-1)*log(x)-(a*p1)*log(b)-log(beta(p1,p2))-(p1+p2)*log(1+(x/b)^a))},0,quint)$value } but I'm facing problems with the quantile function. I tried something like qgbeta2 <- function(proba,b,a,p1,p2) { optimize(function(z)