similar to: Random efftects distribution for nlme

I have been trying to port the extension 'nlme' ("Classes and methods to fit and display linear and nonlinear mixed effects models.")to R found on the Statlib S site. I am having some difficulty. The c code requires at least S.h and nonlin.h. R has S.h but not nonlin.h. I'm only a recent convert to R, and have not used S nor SPlus. Any help is greatly

Hello. I am working on an analysis involving the nonlinear mixed model function (nlme) in R. The data consist of measures of carbon fixation by leaves as a function of light intensity and the parametric function (standard in this area because it has a biological interpretation) is a non-rectangular hyperbola. I cannot get the nonlinear mixed model (nlme) function to converge cleanly. I am

I would appreciate confirmation that the function vcov(model.nlme) gives the var-cov matrix of the fixed effects in an nlme model. Presumably the random-effects var-cov matrix is given by cov(ranef (model.nlme)? Rob Forsyth

Hello. I am trying to fit a nonlinear mixed model involving 3 parameters. I have successfully made a self-starting function. getInitial() correctly outputs the initial estimates. I can also use the nlsList with this function to get the separate nonlinear fits by group. However, I get an error message when using the nlme function. Here is the relevent code:

Hello, I am interested in using nlme to model repeated measurements, but I don't seem to get good CIs. With the code below I tried to generate data sets according to the model given by equations (1.4) and (1.5) on pages 7 and 8 of Pinheiro and Bates 2000 (having chosen values for beta, sigma.b and sigma similar to those estimated in the text). For each data set I used lme() to fit a model,

I am having difficulty understanding the syntax of the nlme() function for nonlinear mixed models. The data frame is called Marouane.chlorophyll. The model involves a dependent variable (Absorb) and an independent variable (Ch.surf), which are both numeric variables in the data frame. The data are hierarchically grouped as Espece, Plante nested within Espece, and Feuille nested within Plante

Dear R-Users, I am comparing the nlme package in S-Plus (v. 7.0) and R (v. 2.2.1, nlme package version 3.1-68.1; the lattice, Matrix, and lme4 have also just been updated today, Jan. 23, 2006) on a PC (2.40 GHz Pentium 4 processor and 1 GHz RAM) operating on Windows XP. I am using a real data set with 1,191 units with at most 4 repeated measures per unit (data are incomplete, unbalanced). I

Dear forum members, What is the formula to calculate denominator degrees of freedom (den df) for nonlinear mixed-effect models with covariates? My model is similar to a CO2 uptake example from Pinheiro and Bates (2000, page 376). In this CO2 dataset, there are two treatments and two types (84 observations in total), but den df for each parameter of the model is 64. Isn’t it too high? Your

This may appear too elementary to some on this list, but not to me. My apologies if this is the case. I have mastered the lme function but the nlme function has me stumped. I am attempting to fit a nonlinear mixed model with 4 levels of nesting. I am getting a cryptic error message and do not know what is wrong with the syntax of the call. This is the call: >

Hello R users, When trying to fit a nonlinear mixed model to a respiration time series, I get the following error message: Error in recalc.varFunc(object[[i]], conLin) : dims [product 30] do not match the length of object [34] In addition: Warning message: In conLin$Xy * varWeights(object) : longer object length is not a multiple of shorter object length Below is an example that generates

Dear all, I try to load the nlme library for Linear and nonlinear mixed effects models by Jose Pinheiro, Douglas Bates and Saikat DebRoy but I get the following error message: > library(nls) > library(nlme) Error in dyn.load(x, as.logical(local), as.logical(now)) : unable to load shared library "C:\Program\R\rw1010/library/nlme/libs/nlme.dll": LoadLibrary failure: Det

Dear all, I am fitting a nonlinear mixed-effects model from a balanced panel of data using nlme. I would like to know whay would be the best options for formally testing for autocorrelation. Is it possible to carry out a Durbin-Watson test on a nlme object? As far as I've seen, I think the durbin.watson function from the car package just works on lm objects. Thank you very much, Antonio

Hi, I have a problem with fitting a nonlinear mixed-effects model to my data. I was able to fit quite simple exponential model but now I?m trying to fit the following Gompertz model: > gomp<-nlme(paino~b0+b1*exp(-exp(-b2*(daydeg.scale-b3))), data=group1, fixed=b0+b1+b2+b3~1, start=c(b0=150, b1=3000, b2=0.6, b3=2500)) I?m getting the following error: Error in chol((value + t(value))/2) :

Hello, I am trying to fit a nonlinear model of the form of: A*x^b*exp(-c*x) This represents a lactation curve. I have a bunch of cows, so I want COW to be a random effect. I have been trying the following code with very littel success: > fm1 <- nlme(yield ~ A*(DIM^B)*(exp(-C*DIM)), + data = group, + fixed = A + B + C ~ 1, + start = c(A = 20, B =

I am looking for R code to be able to fit a linear-linear piecewise model with person-specific changepoint. I have searched the web, but have not been able to locate any code. Below is my attempt at some code: chgpt = function(a1,a2,a3,gam,wave){ yht=numeric(10) y1=(wave <= gam)*(a1+(a2*wave)) y2=(wave > gam)*((a1+(a2-a3)*gam)+a3*wave) yhat=y1+y2 return(yht) } nl.dat <- nlme(y ~

Dear all, I want to do a F test, which involves calculation of the degrees of freedom for the residuals. Now say, I have a nlme object "mod.nlme". I have two questions 1.How do I extract the degrees of freedom? 2.How is this degrees of freedom calculated in an nlme model? Thanks. Jun Shen Some sample code and data =================================================================

Hello R-helpers, I would like to fit a non-linear function to data (Discrete X axis, over-dispersed Poisson values on the Y axis). I found the functions gnlr in the gnlm package from Jim Lindsey: this can handle nonlinear regression equations for the parameters of Poisson and negative binomial distributions, among others. I also found the function nls2 in the software package

Hi there, I am looking to compare nonlinear mixed effects models that have different nonlinear functions (different types of growth curve)embedded. Most of the literature I can find focuses on comparing nested models with likelihood ratios and AIC. Is there a way to compare model fits when models are not nested, i.e. when the nonlinear functions are not the same? Many thanks in advance! Lindsay

I am analyzing a dataset on the effects of six pesticides on population growth rate of a predatory mite. The response variable is the population growth rate of the mite (ranges from negative to positive) and the exploratory variable is a categorical variable (treatment). The experiment was blocked in time (3 blocks / replicates per block) and it is unbalanced - at least 1 replicate per block. I am

I am wondering how to obtain SE estimates for fixed effects from a nonlinear mixed effects model? I have fixed effects corresponding to three factors A, B and C with 2, 3 and 3 levels respectively. I have fit a model of the following general form: nlme1<-nlme(y~ SasympOrig(x, Asym, lrc), data=df, fixed=list(Asym~A*B*C, lrc~A*B*C), start=c(fixef(ETR.nlme)[1], rep(0,17), fixef(ETR.nlme)[2],