similar to: difference in order() between Linux and Windows with mixtures of caps and normal letters

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

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

Can anybody explain me what is going wrong with the rbind command or how I could avoid the problem? I have a script with loops which time has a dataframe as output (called T2sbdata). After each loop I would like to append that dataframe to the results I obtained from the previous loops (called T2sbdataALL) and use for that purpose rbind. Below a part of the loop and the result I get. The

Maybe I do not explain well what I would like to do. I do not want to change the labels of the axis, but the scale. What I want is a general procedure for changing the scale. Its like using a logarithmic scale on a plot. Labels are the same, but the increases of x along the x-axis are defined by a known monotone and continuous function. Florent Bresson ----- Message d'origine ---- De :

SSH, like RSH before it, invokes a command using the user's shell as specified in the passwd file. In a mixed shell environment with some logins csh-like and some sh-like that is sometimes very difficult to handle. (No, I am not fond of csh.) If I could force a single shell everywhere of course that would be preferable but sometimes I have no control over it. I have often wanted an option

An ext3 patch against linux 2.4.10 is at http://www.uow.edu.au/~andrewm/linux/ext3/ This patch is *lightly tested* - ie, it boots and does stuff. The changes to ext3 are small, but the kernel which it patches has recently changed a lot. If you're cautious, please wait a couple of days. The patch retains the buffer-tracing code. This will soon be broken out into a separate patch to make

Dear developers, I am a maintainer of the CORElearn package which uses OpenMP multithreading to speed up some computations. When producing a new release we tested the package with the latest R 2.12.0. On Linux the package works normally. On Windows we installed a recommended version of Rtools (Rtools212) but the linker fails with the messages below. ... g++

Dear All, I have a data as follows: ID <- 1:100 Y <- rnorm(100) X <- rnorm(100) type <- as.factor(rep(1:3,100,time=1)) df <- as.data.frame(cbind(ID, Y,X,type)) I want to plot Y versus X by specifying the pch to be as follows: Subjects having type = 1 must be plotted with a character pch = "A" Subjects having type = 2 must be plotted

Dear all, I believe there is a problem with the corfdrci and the kendallfdrci function from the GeneNT package. The 2nd screening, that is taking what is not in the intersect of the CI and the user-defined MAS criterium does not work properly on my dataset. It seems to work properly on the dataset provided in the library. -- ==================================================================

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

Thanks Ranjan, that provides exactly what I need. I also got a more elaborate answer on stackoverflow (after the same question got rejected form cross validated?) with a running example for this package: https://stackoverflow.com/questions/44825529/package-to-fit-mixtures-of-student-t-distributions/44827220#44827220

Hi R-helpers, I'm trying to model a univariate as a bi-modal normal mixtures. I need to estimate the parameters of each gaussian (mean and sd) and their weights. What's the best way to do this in R? Thanks, Xiao-Jun

Hi, Before I write code to do it does anyone know of code for fitting mixtures of multivariate-t distributions. I can't use McLachan's EMMIX code because the license is "For non commercial use only". I checked, mclust and flexmix but both only do Gaussian. Thanks Nicholas

gamlss.mx can fit these I believe (although no experience with these myself) flexmix may be (relatively easily) adaptable to accomplish this as well hth, Ingmar Ingmar Visser Universitair Hoofddocent ontwikkelingspsychologie | Directeur College Psychologie Afdeling Psychologie | Faculteit Maatschappij- en Gedragswetenschappen | Universiteit van Amsterdam Bezoek | Nieuwe Achtergracht 129B | Kamer

I want to create the mixture formulation of a discrete uniform ie, say f(x) = 1/10, for i = 1,2,3,4,5,6,7,8,9 and 10 and another discrete distribution which has the same values of x, but he probabilities can vary. Can this be done on any package in R? an if so, can the package estimate the 'probabilities' of each of the x value as well as the mixing proportion if I have the data?

Dear R-help, my aim is to fit a constrained 2 component gamma mixture using mix within package mixdist. The constraints being fixing both of the means and both of the sigmas. Thus the only unconstrained parameter I wish to fit is pi the proportions of the mixtures. This is the code I used: PP2Pars<-data.frame(c(0.23,0.77), c(9.174,29.54), c(9.983,12.369));

Hi everybody, I am currently working on mixtures of two densities ( f(xi,teta)= (1-teta)*f1(xi) + teta*f2(xi) ), particularly on the behavior of the variance for teta=0 (so sample only comes from the first distribution). To determine the maximum likelihood estimator I use the Newton-Rapdon Iteration. But when computing the first derivative I get a none linear function (with several asymptotes)

Dear R users Does anyone happen to know a function to fit a Gaussian mixture using *non-linear* constraints?between the parameters? (An EM the allows that will do the job obviously). Thank you in advance -- Jonathan Rosenblatt www.john-ros.com

Dear all, I would like to fit a von mises mixture to my data using the EM Algorithm. Unfornately, existing packages (including circstats) doesn't provide such method. So, does anybody have written such code ? Big thanks, Christophe, (R newbie)

Hi, as you can see in the topic, I am trying to fit a normal mixture distribution with the approach suggested by Hamilton (1991). Since I couldn't find any existing packages including the quasi-bayesian mle, I have to write my own function. Unfortunately, I have absolutely no experience in doing this. If you're not familiar with the QB-MLE, I attached the formula as pdf. The idea