search for: lrc1

Hi there, I'm quite new to R (and statistics), and I like it (both)! But I'm a bit lost in all these packages, so could someone please give me a hint whether there exists a package for fitting exponential curves (of the type t --> \sum_i a_i \exp( - b_i t)) on a noisy signal? In fact monoexponential decay + polynomial growth is what I'd like to try. Thanks in advance,

DeaR I am trying to use a dynamically create formula with nlsList and nlme, but I cannot get the environment of the string-generated formal to work similarly to the manually entered one. Any idea? Dieter #----- library(nlme) # Pinheiro/Bates p 280 fm1Indom.lis = nlsList(conc~SSbiexp(time,A1,lrc1,A2,lrc2), data=Indometh) nlme(fm1Indom.lis,random=pdDiag(A1+lrc1+A2~1)) # works... # Simulating a dynamic formula form = as.formula("conc~SSbiexp(time,A1,lrc1,A2,lrc2)") fm2Indom.lis = nlsList(form,data=Indometh) # still correct nlme(fm2Indom.lis,random=pdDiag(A1+lrc1+A2~1)) #Error i...

Hi, I was trying to run the example of Indomethacin kinetics from the book: ## From Pinheiro/Bates, Mixed-Effects-Models in S and S-Plus, ## Springer, Second Printing 2001, Section 6.2 library(nlme) plot(Indometh) fm1Indom.nls <- nls(conc~SSbiexp(time,A1,lrc1,A2,lrc2), data=Indometh) summary(fm1Indom.nls) plot(fm1Indom.nls,Subject~resid(.),abline=0) ## .... the last plot command gives me the error message: Subject not found in data What point am I missing? Thanks in advance, Hans -- Dr. Hans Mielke Federal Institute for Risk Assessment Thielallee 8...

Hello all! I have a problem to use a biexponential regression model: I use this code: n3<-nls(proc~SSbiexp(cls,a,b,c,d),data=bline) and this is the error message: Error in nls(y ~ cbind(exp(-exp(lrc1) * x), exp(-exp(lrc2) * x)), data = xy, : singular gradient My data is like this: structure(list(proc = c(387.177462830167, 508.090511433077, 321.836817656365, 151.226805860727, 150.885315536942, 86.2895998400175, 56.3215592398958, 39.5044440630984, 25.5703078997907, 7.33494872198676), cls = c...

Following the Indomethicin example in Pinheiro & Bates, chapter 6, page 277 etc, coming to the following comand: fm2Indom.nlme <- update( fm1Indom.nlme, random = pdDiag(A1 + lrc1 + A2 ~ 1) ) debugging nlme gives the following output: Browse[1]> n debug: modelResid <- ~eval(model, data.frame(data, getParsNlme(plist, fmap, rmapRel, bmap, groups, beta, bvec, b, level, N)))[naPat] Browse[1]> n debug: ww <- eval(modelExpression[[2]], envir = nlEnv) Browse[1]&g...

At the top of page 283 of Pinheiro and Bates, a covariance structure for the indomethicin example is specified as random = pdDiag(A1 + lrc1 + A2 + lrc2 ~ 1) The argument to pdDiag() looks like a two-sided formula, and I'm struggling to reconcile this with the syntax described in Ch4 of the book and online. Further down page 283 the formula is translated into list(A1 ~ 1, lrc1 ~ 1, A2 ~ 1, lrc2 ~ 1) which I find just as puzzling....