similar to: Follow-up on nls convergence failure with SSfol

Dear list, I do have a problem with nls. I use the following data: >test time conc dose 0.50 5.40 1 0.75 11.10 1 1.00 8.40 1 1.25 13.80 1 1.50 15.50 1 1.75 18.00 1 2.00 17.00 1 2.50 13.90 1 3.00 11.20 1 3.50 9.90 1 4.00 4.70 1 5.00 5.00 1 6.00 1.90 1 7.00 1.90 1 9.00 1.10 1 12.00 0.95 1 14.00

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 am trying to gain some experience with the function gnls from the nlme package. I tried to model the Theophyline data by trying to model the presumed dependency of the clearance on the body weight. This is my function call of gnls: gnls(conc~SSfol(Dose,Time,lKe,lKa,lCl),data=Theoph, params=list(lKe~1,lKa~1,lCl~Wt),start=c(-2.4,0.46,-3.22,0.01)) That's been the result: Error

I was looking for all the glm-related 'family' functions in stats using the following predicate that returns TRUE for any function whose first argument is called "link". is.family <- function(object) is.function(object) && identical(names(as.list(object))[1], "link") It threw an error when applied to SSfol > is.family(SSfol) Error in

Dear friends of nlme, Running quinModel (Pinheiro/Bates page 380) on R (current release, windows) gives: Nonlinear mixed-effects model fit by maximum likelihood Model: conc ~ quinModel(Subject, time, conc, dose, interval, lV, lKa, lCl) Data: Quinidine Log-likelihood: -497 Fixed: lV + lKa + lCl ~ 1 lV lKa lCl 5.382 -0.273 2.470 Random effects: Formula: list(lV ~ 1, lCl ~ 1)

This concerns the "Clinical Study of Quinidine" example on page 380 of the book "Mixed-Effects Models in S and S-PLUS" by Pinheiro and Bates (2000). I have tried to reproduce the example, but get an error: > library(nlme) > fm1Quin.nlme <- nlme(conc ~ quinModel(Subject, time, conc, dose, interval, lV, lKa, lCl), + data=Quinidine, +

Greetings, I would like to use a cubic spline or smoother to model the fixed effects within nlme. So far the only smoother I have been able to get to run successfully in nlme is smooth(). I tried smooth.spline: fixed=list(lKa~1,lCL~smooth.spline(BSA, df=3)) the error I got was the following. Error in model.frame(formula, rownames, variables, varnames, extras, extranames, : invalid

I try to fit reaction kinetic data to a given hypothetical model consisting of 3 ODEs. After some reading in Bates/Watts and the literature cited there (e.g. Jennrich/Bright) I looked in R for functions that support the use of the matrix exponential method. Until now I used for a similar (but simpler) problem the nls package and fitted against the the parameterized solution function. But this

https://bugzilla.mindrot.org/show_bug.cgi?id=1936 Bug #: 1936 Summary: -A command not available from ~C Classification: Unclassified Product: Portable OpenSSH Version: 5.8p1 Platform: All OS/Version: All Status: NEW Severity: enhancement Priority: P2 Component: ssh AssignedTo:

https://bugzilla.mindrot.org/show_bug.cgi?id=1937 Bug #: 1937 Summary: Make it possible to give a give an ssh session only access to a limit subset of ssh-agent keys Classification: Unclassified Product: Portable OpenSSH Version: 5.8p1 Platform: All OS/Version: All Status: NEW Severity:

Hello, I am very new in R so I am so sorry for this question. I have the Barro-Lee data set which contains 98 countries and I want to run the regressions only for the Latin America countries, so what do you recomend? How can I delete all the other countries or how can I select the countries of Lat. Am. thank you this is the list of countries SHCODE COUNTRY NAME WBCTRY

Hello, I came across a problem when building a randomForest model. Maybe someone can help me. I have a training- and a testdataset with a discrete response and ten predictors (numeric and factor variables). The two datasets are similar in terms of number of predictor, name of variables and datatype of variables (factor, numeric) except that only one predictor has got 20 levels in the training

Say I have the following data: testDat <- data.frame(A = c(1,NA,3), B = c(NA, NA, 3)) > testDat A B 1 1 NA 2 NA NA 3 3 3 rowsums() with na.rm=TRUE generates the following, which is not desired: > rowSums(testDat[, c('A', 'B')], na.rm=T) [1] 1 0 6 rowsums() with na.rm=F generates the following, which is also not desired: > rowSums(testDat[, c('A',

R-helpers, Below is a simple example of some output that I am getting while trying to work with a data frame in R 2.12.1 for Mac. ----- > testdat <- data.frame(matrix(ncol=10, nrow=10)) > colnames(testdat) <- c('a','b','c','d','e','f','g','h','i','j') > testdat[seq(1,10,3),] <-

Hi, I am experimenting with the function predict() in two versions of R and the R extension package "survival". library(survival) set.seed(123) testdat=data.frame(otime=rexp(10),event=rep(0:1,each=5),x=rnorm(10)) testfm=as.formula('Surv(otime,event)~x') testfun=function(dat,fm) { predict(coxph(fm,data=dat),type='lp',newdata=dat) } # Under R 2.11.1 and

Hi, I am experimenting with the function predict() in two versions of R and the R extension package "survival". library(survival) set.seed(123) testdat=data.frame(otime=rexp(10),event=rep(0:1,each=5),x=rnorm(10)) testfm=as.formula('Surv(otime,event)~x') testfun=function(dat,fm) { predict(coxph(fm,data=dat),type='lp',newdata=dat) } # Under R 2.11.1 and

Dear R users, I'm having some problems with the stack() and unstack() functions, and wondered if you could help. I have a large data frame (400 rows x 2000 columns), which I need to reduce to a single column of values (and therefore 800000 rows), so that I can use it in other operations (e.g., generating predictions from a GLM object). However, the problem I'm having can be reproduced

Get it here: http://script.aculo.us/downloads Short take on what''s new: -> Autocompletion took a notch up with incremental and local (js array) functionality -> Capability to remove draggables/droppables and redeclare sortables -> Effect.ScrollTo -> Fix memory leaks in IE and Gecko -> Make some 3rd-party js libraries comaptible, namely IE7.js -> Various tweaks and

I am trying to get R to resample my dataset of two columns of age and length data for fish. I got it to work, but it is not resampling every replicate. Instead, it resamples my data once and then repeated it 5 times. Here is my dataset of 9 fish samples with an age and length for each one: Age Length 2 200 5 450 6 600 7 702 8 798 5 453 4 399 1 120 2 202 Here is my code which resamples my

Say I have a tab-delimited table I want to read into R. What should I expect to happen if some of the entries contain the character " ' "? I thought it would read the file fine, but that is not what happens. Instead, all the values in between two " ' "s get read into one field, and things are just seriously messed up. Is this a bug, and besides removing the offending