similar to: lme with log-normal distribution of parameters

Dear R-Users, I have a question concerning extraction of parameter estimates of variance function from lme fit. To fit my simulated data, we use varConstPower ( constant plus power variance function). fm<-lme(UPDRS~time,data=data.simula,random=~time,method="ML",weights=varConstPower(fixed=list(power=1))) I extract the results of this function by using the following codes:

Hi I am having some problems running a covariate analysis with my colleage using R with the NonMem program we are using for a graduate school project. R and NonMem run fine without adding in the covariates, but the program is giving us a problem when the covariate analysis is added. We think the problem is with the R code to run the covariate data analysis. We have the control stream, R code

Dear r-helpers, I downloaded http://popgen.unimaas.nl/~jlindsey/rcode/rmutil.tar (it was originally .tgz, but got unzipped by my browser). Can anyone give me detailed instructions on installing this and Lindsey's other packages on R version 2.4.0 (2006-10-03)---(powerpc- apple-darwin8.7.0, locale: C)? _____________________________ Professor Michael Kubovy University of Virginia

Hello, I have made an R script that prepares a NONMEM dataset and I would like to start the NONMEM run right after the dataset is ready. I am using windows XP, R 2.9.1 and NONMEM 6. I have prepared a run.bat file that looks like this: ---------------------------------------- call K:\nmvi\NMdirectories.bat call K:\nmvi\nmfe6 "path\control.txt" "path\output.txt"

Hello, I was asked to try the following code on R, gamma.mles function (xx,shape0,rate0) { n<- length(xx) xbar<- mean(xx) logxbar<- mean(log(xx)) theta<-c(shape0,rate0) repeat { theta0<- theta shape<- theta0[1] rate<- theta0[2] S<- n*matrix(c(log(rate)-digamma(shape)+logxbar,shape/rate-xbar),ncol=1) I<- n*matrix(c(trigamma(shape),-1/rate,-1/rate,shape/rate^2),ncol=2)

Hi, I've noticed I get different results fitting a function to some data on my laptop to when I do it on my computer at work. Here's a code snippet of what I do: ##------------------------------------------------------------------ require(circular) ## for Bessel function I.0 ## Data: dd <- c(0.9975948929787, 0.9093316197395, 0.7838819026947, 0.9096108675003, 0.8901804089546,

Dear group, I am trying to prepare a NONMEM friendly dataset for population PK analysis. My patient IDs are 10 digit long and NONMEM is losing precison and rouding the last couple of digits. I need to generate unique Patient IDs fromt he current 10-digit IDs. Ihave total 250 subjects so I appreciate if anybody can suggest me a way to code this in R. Regards, Ayyappa [[alternative HTML

In the following code I have created the posterior density for a Bayesian survival model with four parameters. However, when I try to use the adapt function to perform integration in four dimensions (on my old version of R I get an error message saying that I have applied a non-function, although the function does work when I type kernel2(param0, theta0), or on the newer version of R the computer

Hi All, I want to upload J K Lindsey's "repeated" in a LINUX OS.. I had tried the command.. [root@localhost Desktop] # R CMD INSTALL repeated.gz " WARNING: invalid package 'repeated' " *Installing to library '/usr/local/lib/R/library' ERROR: No packages

I would like to install the package "growth" as it contains the function "corgram" and some other presumably useful stuff for time series analysis. I can see it is in R standard library list: http://hosho.ees.hokudai.ac.jp/~kubo/Rdoc/doc/html/packages.html<http://hosho.ees.hokudai.ac.jp/%7Ekubo/Rdoc/doc/html/packages.html>

Hello! I must estimate the parameters of a exponential power density. There is the normalp package, but this works only for a shape parameter bigger than 1. But what should i do if the shape parameter is less than 1? (Sorry for my english) Thank you very much for help! -- View this message in context: http://www.nabble.com/Parameters-of-exponential-power-density-tp20774495p20774495.html Sent from

*Dear R-help: My name is Rodrigo and I have a question with nlme package in R to fit a mixed beta regression model. The details of the model are: Suppose that:* *j in {1, ..., J}* *(level 1)* *i in {1, ..., n_j}* *(level 2)* *y_{ij} ~ Beta(mu_{ij} * phi_{ij}; (1 - mu_{ij}) * phi_{ij}) y_{ij} = mu_{ij} + w_{ij} * *with* *logit(mu_{ij}) = Beta_{0i} + Beta_{1i} * x1_{ij} + b2 * x2_{ij}

Dear all, I want to min "integrate( (p1*dnorm+p2*dnorm+p3*dnorm)^(1.3))" for p, mu, and sigma. So, I have to estimate 8 parameters(p3=1-p1-p2). I got this warning-"Error in integrate(numint, lower = -Inf, upper = Inf) : non-finite function value." My questions are How could I fix it? I tried to divide into several intervals and sum up, but I got same message. My code is

Hi, I am looking for some help regarding the use of the mle function. I am trying to get mle for 3 parameters (theta0, theta1 and theta2) that have been defined in the the log-likelihood equation as theta0=theta[1], theta1=theta[2] and theta2=theta[3]. My R code for mle is: mle(Poisson.lik, start=list(theta=c(20,1,1), method="Nelder-Mead", fixed=list(w=w, t1=t1, t2=t2)) But I keep

Dear R users I am trying to use OPTIMX(OPTIM) for nonlinear optimization. There is no error in my code but the results are so weird (see below). When I ran via OPTIM, the results are that Initial values are that theta0 = 0.6 1.6 0.6 1.6 0.7. (In fact true vales are 0.5,1.0,0.8,1.2, 0.6.) -------------------------------------------------------------------------------------------- >

Oh, sorry; I changed signs in the model, fitting theta0 + theta1*exp(theta2*x) So for theta0 - theta1*exp(-theta2*x) use theta1= -.exp(-1.8) and theta2 = +.055 as starting values. -- Bert On Sun, Aug 20, 2023 at 11:50?AM Paul Bernal <paulbernal07 at gmail.com> wrote: > Dear Bert, > > Thank you so much for your kind and valuable feedback. I tried finding the > starting

Dear R users, I used to "OPTIM" to minimize the obj. function below. Even though I used the true parameter values as initial values, the results are not very good. How could I improve my results? Any suggestion will be greatly appreciated. Regards, Kathryn Lord #------------------------------------------------------------------------------------------ x = c(0.35938587,

Dear R users, I used to "OPTIM" to minimize the obj. function below. Even though I used the true parameter values as initial values, the results are not very good. How could I improve my results? Any suggestion will be greatly appreciated. Regards, Kathryn Lord #------------------------------------------------------------------------------------------ x = c(0.35938587,

Hi all, Does anyone know what happened to the dna library or the dotmatrix function? For the life of me, I can't find it anywhere with the exception of this reference: http://rss.acs.unt.edu/Rdoc/library/dna/html/dotmatrix.html Thanks! Jeff. http://www.nd.edu/~jspies/ [[alternative HTML version deleted]]

Hello - I cannot get to www.alpha.luc.ac.be/~jlindsey/rcode.html<http://www.alpha.luc.ac.be/%7Ejlindsey/rcode.html>to obtain and install the repeated library for use of glmm(). Is the web page not active? Can you give me an alternative location to obtain the repeated library? Thank you, Becky Parker [[alternative HTML version deleted]]