similar to: NLME Fitting

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

I am trying to mimic the SAS code below in R. The trick is that each row in the dataset has variable "t" which controls how many times the do-loop below will be iterated (that is, the model is fit to the response, ifate, 0 to t-1 times for each row of data). Is it possible to incorporate a loop like this into nlme by writing a function? Can anybody provide some hints to get me on my

Dear Dr. Bates, Thank you very much for your response. I had consulted the algorithm described in Pinheiro and Bates. However, what I don't understand (among other things) is why my two parameters appear to be estimated at different grouping levels (based on the DF values). Affect this different values of DF at the estimates parameters? The estimates fixed effects were get at the same level of

Hi, I would like to fit a model for a factorial design that allows for unequal variances in all groups. If I am not mistaken, this can be done in lm by specifying weights. A function intended to specify weights for unequal variance structures is provided in the nlme library with the varIdent function. Is it apropriate to use these weights with lm? If not, is there another possibility to do

On 11 May 2017 at 10:17, Erwan Le Pennec wrote: | Dear all, | | I've stumbled a similar issue with the package cluster when | compiling the 3.4.0 version with the settings of Fedora RPM specs. | Compiling R with the default setting of configure yields a version that | works for cluster... and nlme. | | I did not find the exact option that was the cause of this issue | but

Dear listserv members, In Croissant (2008) “Panel Data Econometrics in R: The plm Package” the authors seem to indicate that the nlme package for R cannot correctly handle unbalanced panel data: “Moreover, economic panel datasets often happen to be unbalanced (i.e., they have a different number of observations between groups), which case needs some adaptation to the methods and is not

lme() and gls() models from the nlme package are all crashing with R.3.4.0. Identical code ran correctly, without error in R 3.3.3 and earlier versions. The behavior is easily demonstrated using one of the examples form the lme() help file, along with two simple variants. I have commented the errors generated by these calls, as well as the lines of code generating them, in the code example below.

Dear all, I am analyzing some data that requires a mixed model. I have been reading Pinheiro and Bates' book, but cannot find the notation to fit the following model: Suppose I have the dataset below. Here I am fitting variable p as a fixed effect, variable h as a random effect and variable t as nested within h. I would like to include the variable j as well as an independent (non-nested)

Hi all, I have a questions regarding mixed effects models: I'm trying to plot e.g. fitted vs residuals for each level of the random effects, and i'm getting the same error. I guess this might be a problem of the graphic capabilities of R. Is there any way to obtain those plots? library(nlme) attach(ergoStool) names(ergoStool) [1] "effort" "Type"

Dear list, Has anyone created a version of SSmicmen that allows testing for group differences? The basic Michaelis-Menten equation is: (Bmax * X) / (Kd + X). The nlme package allows modeling of random effects for Bmax and Kd as needed, but I curious how I can build in group differences? I have receptor binding data for strains of mice, and following Pinheiro and Bates' lead in their

Hi all! Is there a function that provides the VarCov matrix for a nlme objects? How I can extract the matrix for a nlme model fitted? I would appreciate any guidance Regards Lic. Gabriela Escati Pe?aloza Biolog?a y Manejo de Recursos Acu?ticos Centro Nacional Patag?nico(CENPAT). CONICET Bvd. Brown s/n?. (U9120ACV)Pto. Madryn Chubut Argentina Tel: 54-2965/451301/451024/451375/45401 (Int:277)

Hi, I'm trying to fit a model using variance components in R, but if very new on it, so I'm asking for your help. I have imported the SPSS database onto R, but I don't know how to convert the commands... the SPSS commands I'm trying to convert are: VARCOMP RATING BY CHAIN SECTOR RESP ASPECT ITEM /RANDOM = CHAIN SECTOR RESP ASPECT ITEM /METHOD = MINQUE (1) /DESIGN

Hi, I'm fitting mixed effects models using the lme function of the nlme package. This involves using the various associated plot functions. However, when I attempt to fit a number of models using an loop, whilst the models work, the plot functions fail. As a trivial example, the following works: library(nlme) graphics.off() x<-c(1:10) y<-c(1:4,7:12)

Dear friends. Below is ouput directly from the help on qqnorm.lme.html It do not seem to work as expected - on win98, R 1.1, although the regression is undertaken, so qqnorm misunderstands, or what ? library(nlme) data(Orthodont) fm1 <- lme(distance ~ age, Orthodont, random = ~ age | Subject) # normal plot of standardized residuals by gender qqnorm(fm1, ~ resid(., type = "p") | Sex,

Hi, Well after trying to fix the assign commands in version 3.1.7 of your nlme package I still cannot get the plot functions to work. Basically I have no other packages installed (apart from those provided with R) so nlme is the first. my R version info is; platform sparc-sun-solaris2.7 arch sparc os solaris2.7 system sparc, solaris2.7 status

Among others, datam contains the columns: logconc, tm, dose, subj, bilirubin. None of these are factor variables. The following compartment models work (the first still has not converged after 100 interations): res1 <- nlme(logconc~p2+p3+log(dose/(exp(p1)-exp(p2))* (exp(-exp(p2)*tm)-exp(-exp(p1)*tm))),start=list(fixed=c(5,-2,-0.1)), fixed=list(p1+p2+p3~1),control=list(maxIter=100),

Hello , I am hoping for some advice. I want to run a repeated measures ANOVA. The primary problem is that my attempt to remove missing values created a dataset of missing values. The data set consists of 92 rows (1 row per participant) x 186 variables. The steps of the analysis undertaken are outlined below (#). Any assistance is appreciated in relation to how to remove the missing values so

dear list: I used the nlme library according to the great Pinheiro/Bates book, on R2.3, WinXp Lac.lme is an lme object with unbalanced data, group is a factor variable with three levels, when I tried to plot the residuals by group I got this error msg: >plot(Lac.lme,resid(.,type='p')~fitted(.)|group) Error in limits.and.aspect(prepanel.default.xyplot, prepanel = prepanel, :

Hello, nls-users, is it possible to pass additional parameters to the model function that are known and groupwise constant with nlsList? I could not find something like a "keep this fixed" option in the documentation and the code (my fault...?) The current workaround is to break the problem down into groups and use globals to pass the constant parameters, but it is ugly code and

Dear All, let E(Y | t, b, theta) be the conditional expectation of Y where b is a vector of random effects , theta is a vector of fixed effects and t is the time of observation (t =1,2, ...,n). I wonder if nlme has a function to compue E(Y | t, theta). I know that it can be done by approximating the integrals over b of E(Y | t, b, theta). But I am wondering if nlme has a function