similar to: nlme question

I am running into problems calling the library function nlme from within another function. Basically,the following function (with v a list containing data and initialization values) > testfunc function(dat=v) { test<-nlsList(result~a+(b-a)/(1+(conc/(c+z*cdiff))^d) |rep,start=dat$init,data=dat$mixeddat) return(nlme(test,random=b~1)) } produces the error message Error in eval(expr, envir,

I hope that the mailing list is the correct forum for the question below. I have trouble calling functions nlsList and nlme from another function. Any help would be greatly appreciated. Jens Praestgaard Human Genome Sciences Rockville MD. I have a data set v with two components, v$mixeddat and v$init. They are listed below: > v$mixeddat conc result rep sample z 11 20.00000000

I apologize for posting on this question again, but unfortunately, I don't have and can't get access to MASS for at least three weeks. I have found some code on the web however which implements the prediction error algorithm in cv.glm. http://www.bioconductor.org/workshops/NGFN03/modelsel-exercise.pdf Now I've tried to adapt it to my purposes, but since I'm not deeply familiar

Hi, I'm using metafor to perform a mixed-effects meta-analysis. I'd like to test whether the effect is different for animals and plants/whether "group" (animal/plant) influences the effect size, but am having trouble interpreting the results I get. I've read previous posts about QM in metafor, but I'm still a bit confused. I've dummy-coded the factors:

Hi, I'm trying to fit a multinomial logistic regression to my data which consists of 5 discrete variables (scales 1:10) and 1000 observations. I get the following error: Error in `row.names<-.data.frame`(`*tmp*`, value = c("NA.NA", "NA.NA", : duplicate 'row.names' are not allowed In addition: Warning message: non-unique value when setting

*I have the following function:* /plot_mi_time = function(mdata, miname) { mdata2 = mdata[row.names(hakat) == miname, ] print(mdata2) xcoords <- c(1,1,2,2,3,3,4,4,5,5,6,6) plot(c(xcoords), mdata2, xaxt="n", ylab="Expression", xlab="Time(h)", , main=miname) axis(1, at=xcoords,

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 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))

Hi, I want to control the plots in the output of the xyplot(). It is easier to explain it through an example: #------------------------------------------------------------- library(lattice); # months months <- c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep",

Hi, I have the following function that i use to plot graphs. plot_mi_time = function(mdata, miname) { mdata2 = mdata[row.names(mir_test3) == miname, ] # print(mdata2) xcoords <- c(1,1,2,2,3,3) plot(xcoords, mdata2, xaxt="n", ylab="Expression", xlab="Time(h)", , main=miname) axis(1, at=xcoords,

Hello, How do I specify the formula and random effects without a startup object ? I thought it would be a mixture of nls and lme. after trying very hard, I ask for help on using nlme. Can someone hint me to some examples? I constructed a try using the example from nls: #variables are density, conc and Run #all works fine with nls DNase1 <- subset(DNase, Run == 1 ) fm2DNase1 <- nls(

Dear listers, I am trying to fit a model using nlsList() using alternately a SSfol() selfstart function or its developped equivalent formulae. This preliminary trial works well mydata<-groupedData(Conc~Tps|Organ,data=mydata) mymod1<-nls(Conc~SSfol(Dose,Tps,lKe,lKa,lCl),data=mydata) as well as a developped form: mymod2<-nls(Conc~Dose * exp(lKe+lKa-lCl) *

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),

Hi All I'm analysing growth rates using a gompertz (logistic) curve and am attempting to fit parameters for all of my study birds using nlsList. I've been looking for an option in nlsList to set min and max limits for parameter values during estimation, although I have failed to find any under 'control'. Other users seem to have reported that using control in the port algorithm

R Users, I am new to R and have tried to figure out how to automate this process instead of using excel. I have read in this dataframe into r with read.table. I need to reshape the data from the first table into the format of the second table. TractID StandID Species CruiseDate DBHClass TreesPerAcre Carbon Stand 1 Loblolly Pine 5/20/2010 10 1.2 Carbon Stand 1 Loblolly Pine

Hi all, I need to replace missing values in a matrix by 10 % of the lowest available value in the matrix. I've got a function I've used earlier to replace negative values by the lowest value, in a data frame, but I'm not sure how to modify it... nonNeg = as.data.frame(apply(orig.df, 2, function(col) # Change negative values to a small value, close to zero { min.val =

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

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

Hallo! I want to plot multiple grouped data in a postscript file using a loop. As I use a loop no plot (or just one empty plot) is generated. Here an example: library(nlme) data(Loblolly) # example data from nlme postscript("PSFile.ps") for (i in 1:1) # just as example { plot(Loblolly) } dev.off() Result: Just an empty PSFile.ps. (Withoput the loop it works. May anybody help? Karl

Hi all, I have a pretty basic question about categorical variables but I can't seem to be able to find answer so I am hoping someone here can help. I found that if the factor names are all in numbers, fitting the model in lm would return labels that are not very recognizable. # Example: let's just assume that we want to fit this model fit <- lm(height ~ age + Seed,