similar to: Problem with a while loop embedded in a function.

I ran into a problem trying to make a plot from a file that's read using source. Basically, I have the following code in a file "plot.R" : library(nlme) data(Loblolly) fm1 <- nlme(height ~ SSasymp(age, Asym, R0, lrc), data = Loblolly, fixed = Asym + R0 + lrc ~ 1, random = Asym ~ 1, start = c(Asym = 103, R0 = -8.5, lrc = -3.3))

Hola a todos Les consulto por un problema con xtable y nlme, tomando un ejemplo del manual de nlme para obtener los resultados en latex utilizando xtable, se puede utilizar el siguiente código, pero hay un problema y causa error. library(nlme) library(xtable) fm1 <- nlme(height ~ SSasymp(age, Asym, R0, lrc), data = Loblolly, fixed = Asym + R0 + lrc ~ 1,

Hi All. I'm trying to run nlsList an getting an error that makes no sense to me. I have accuracy and reaction time data over many trials for each person (id) When I use nlsList code that is virtually identical to the example in the doc file I get the following error. I've tried everything I could think of and can't get around it. Any ideas what I'm doing wrong? **************

I need your help to make R works on my linux box, runing fedora 11. Few things on the machine and steps I did: 1. uname -a shows: Linux bagvapp 2.6.29.4-167.fc11.i586 #1 SMP Wed May 27 17:14:37 EDT 2009 i686 athlon i386 GNU/Linux 2. it has a gcc (version 4.4) RedHat's build 3. the g77 comes with the box does not work (R's configure tells it could not compile simple fortran code); so

Am Dienstag, 25. April 2017, 11:21:31 schrieb Dirk Eddelbuettel: > On 25 April 2017 at 16:11, Johannes Ranke wrote: > | This looks similar to what I got this morning when I tested my > | (unreleased) > | backport of R 3.4.0 to Debian jessie. My test was > | > | library(MASS) > | example(rlm) > | > | and there was an object that was not found. I am on a train on the way

Mmmh, seems as if I really should change my options as I seem to keep sending off empty bug-reports ;-/ Sorry guys. Here is the content that should have been in the last e-mail: `R CMD check nlme' fails on my machine. The final output in nlme-Ex.Rout is: > library(nlme) > data(Soybean) > fm1 <- nlme(weight ~ SSlogis(Time, Asym, xmid, scal), data = Soybean, + fixed =

Hi list, In the object returned by summary.nlsList, what's the difference between "coefficients" and "parameters"? The have the same "Estimate", different se (therefore t value), but same p values. R.2.8.0 on winxp with nlme_3.1-89 Thanks, ...Tao +++++++++++++++++++++++++++++++++++++++++++++++++ > library(nlme) > fm1 <- nlsList(uptake ~

I have a question about the lme function in R. My question is: After I got the object from function lme, why the numIter value of the object is always NULL? Following is my code: jjww<-lme(y~x*zz,data=simul,random=~x|group, control=lmeControl(returnObject=TRUE)) attributes(jjww) jjww$numIter the first 20 observation of data simul are: > simul y

Hi, I have a question about the lme function in R. My question is: After I got the object from function lme, why the numIter value of the object is always NULL? Following is my code: jjww<-lme(y~x*zz,data=simul,random=~x|group, control=lmeControl(returnObject=TRUE)) attributes(jjww) jjww$numIter the first 20 observation of data simul are: > simul y

I have a need to call and pass arguments to nlme() from within another function. I use R version 1.8. I have found an apparent way to make this work, but I would appreciate some comments on whether this fix is really appropriate, or there is another way to do it that does not involve changing the source code. I don't have enough experience to start changing the sorurce code of a library

How to set the nlme() function to return the answer without the intercept parametrization? #========================================================================================= library(nlme) Soybean[1:3, ] (fm1Soy.lis <- nlsList(weight ~ SSlogis(Time, Asym, xmid, scal),                        data = Soybean)) (fm1Soy.nlme <- nlme(fm1Soy.lis)) fm2Soy.nlme <- update(fm1Soy.nlme,

I am having trouble fitting correlation structures within nlme. I would like to fit corCAR1, corGaus and corExp correlation structures to my data. I either get the error "step halving reduced below minimum in pnls step" or alternatively R crashes. My dataset is similar to the CO2 example in the nlme package. The one major difference is that in my case the 'conc' steps are

When I run gnls I get the error: Error in nls(y ~ cbind(1, 1/(1 + exp((xmid - x)/exp(lscal)))), data = xy, : step factor 0.000488281 reduced below 'minFactor' of 0.000976563 My first thought was to decrease minFactor but gnlsControl does not contain minFactor nor nlsMinFactor (see below). It does however contain nlsMaxIter and nlsTol which I assume are the analogs of

Dear R-Help, I'm trying to fit a model of the following form using gnls. I've fitted it using nlsList with the following syntax: nlsList(Y~log(exp(a0-a1*X)+exp(b0-b1*X))|K,start=list (a0=6,a1=0.2,b0=4.5,b1=0.001),data=data.frame(Y=y,X=X,K=k))) which works just fine: <snip> Coefficients: a0 a1 b0 b1 1 5.459381 0.5006811 5.137458 -0.0040548687

Better posted on r-sig-mixed-models , no? Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Wed, Aug 23, 2017 at 5:17 AM, PIKAL Petr <petr.pikal at precheza.cz> wrote: > Dear all > > I encountered strange

Hello, I am trying to fit a nlme (non linear mixed effect). I am using the SelfStart function SSlogis. However the data in my hand contains few observations per subject (4 or less), so the nlsList doesn't work... In this case I should fixe initial parameter estimates. I remark that values of initial estimates have a greater effect on the model fit (i.e. loglikelihood, AIC and also on

I am trying to learn how to use nlme by working on a simple example. I attach the data from a toy example I made up which is similar to my real problem. (My grasp of fixed/random effects is still a bit tenuous) It is a longitudinal study of the effect of two treatments: A and B. The data were created by: A: y<-12/(1+exp((2-time)/.5)),y<-8/(1+exp((2-time)/.5)) B:

Dear all I encountered strange behaviour of augPred with virtually the same data First I made groupedData object. > mar.g<-groupedData(rutilizace~doba|int, data=mar) When I perform nlme on complete dataset I get an error with augPred > fit<-nlsList(rutilizace~SSasymp(doba, Asym, R0, lrc), data=mar.g) Warning message: c("1 error caught in nls(y ~ cbind(1 - exp(-exp(lrc) * x),

> On Aug 23, 2017, at 8:08 AM, PIKAL Petr <petr.pikal at precheza.cz> wrote: > > Hi > > Well, yes I tried it about two weeks ago but my post did not get through as it still awaits moderator approval. It got through just fine. It appeared on Aug 15. It just didn't get any replies. As I read your original question in this thread, it was not clear to me that you had

Hi All. I'd like to send some control arguments to the nls function when performing a nlsList analysis. I'm fitting a power model to some grouped data and would like to impose lower bounds on the estimates using the "port" algorithm. Obtaining the lower bound constraint works fine with a direct call to nls for a single level of the grouping variable. ?However, the bounds