search for: ssasymp

Dear R Help, At the risk of sounding na?ve, is there a way for obtaining something resembling an r^2 value for the fit obtained using SSasymp? I have read ?SSasymp and looked through the archives but to no avail. Many thanks, Robert Terwilliger

Hi, I'm a new R user, with a lot of questions. At the moment I'm stoped on an error traying to fit a model: > x <- sandeel ## numeric data (2500-60000) > y <- Noss ## numeric data (0-1.2) > A <- 0.8 > B <- 0.6 > C <- 1/40000 > nls( y ~ A-B*exp(-C*x)) Error in match.call(definition, call, expand.dots) : .Primitive... is not a function I'm

Hi, I have a program written in R which is good on the version 1.2, but for the fallowing versions of R, an error always is at the same place. That is at the level of the fallowing line: Sur<- getInitial(res2[m:M,2]~SSasymp(res2[m:M,1],Asymp,resp0,lrc),data=res2) Error in eval(expr,envir,enclos):numeric envir arg not of length one I don't know at all this langage for the instant. Thanks, Christelle ------------------------------------------------------------- NetCourrier, votre bureau virtuel sur Internet...

...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? ************** fm.nls<-nlsList(RT ~ SSasymp(trial, Asym, R0, lrc) , data = df.group, na.action="na.exclude", start = c(Asym = 550, R0 = 770, rc =-2.5)) "Error in nlsList.formula(RT ~ SSasymp(trial, Asym, R0, lrc), data = df.group, : Data must be a gr...

Please help getting the R squared value in asymptotic regression model I use the code below model1<-nls(GN1~SSasymp (nrate,a,b,c), data = data.1 ) and R produced the modell coefficients without the R squared value? -- Ahmed M. Attia Research Assistant Dept. Of Soil&Crop Sciences Texas A&M University ahmed <ahmedatia@zu.edu.eg>.attia@ag.tamu.edu Cell phone: 001-979-248-5215 [[alternative HT...

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)) windows(6,6) plot(fm1) This code is taken from the help page for 'nlme'. If I cut an paste this code into the...

Hello I?m need fitt growth curve with data length-age. I want to evaluate which is the function that best predicts my data, to do so I compare the Akaikes of different models. I'm now need to evaluate if changing the initial values changes the parameters and which do not allow to estimate the model. To do this I use the function nls(); and I randomize the initial values (real positive number).

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, random = Asym ~ 1, start = c(Asym = 103, R0 = -8.5, lrc = -3.3)) summary(fm1) xtable(summary(fm1)) Por si prefieren no ejecutar el código, el mensaje de error es: Error en UseMethod(&...

...el** * * below is the equation of the model (Reference the R book page 662)* y = a - b e^-cx when I compensate x with 50 for instance, I get a very high value does not match the graph produced by the same model (Asymptotic regression model). below is the output analysis from R; Formula: GN1 ~ SSasymp(nrate, a, b, c) Parameters: Estimate Std. Error t value Pr(>|t|) a 12.8190 0.4407 29.09 8.92e-05 *** b 5.7249 0.2803 20.42 0.000257 *** c -4.6697 0.1703 -27.41 0.000107 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.28...

Dear Rusers, How would I plot several (24) fitted curves (nonlinear least squares) within a single plot? To get the parameters I use: resff <- list() for (s in levels(PairID)) { resff[[s]] <- nls(Photo ~ SSasymp(Ci, Asym, lrc, c0), subset = (PairID == s)) } Is it also possible to plot two different groups (male, female) of curves in the same plot, with different style lines? Many thanks, Stewart -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list --...

Hi there are some predefined self-start functions, like SSmicmen, SSbiexp, SSasymp, SSasympOff, SSasympOrig, SSgompertz, SSflp, SSlogis, SSweibull, Quadratic, Qubic, SSexp (nlrwr) Btw, do you know graphic examples for this functions? The SSexpDecay (exponential decay) for y = (y0 - plateau)*exp(-k*x) + plateau from http://stats.stackexchange.com/questions/17126/how-can-i-make-m...

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), exp(-exp(lrc) * x)), data = xy, : singular gradient", "1 error caught in start = list(lrc = lrc), algorithm = \"plinear\"): singular gradient") > fit1&...

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

Hello there, I am trying to fit an exponential model using nls to some data. #data t <- c(0,15,30,60,90,120,240,360,480) var <- c(0.36,9.72,15.50,23.50,31.44,40.66,59.81,73.11,81.65) df <- data.frame(t, var) # model # var ~ a+b*(1-exp(-k*t)) # I'm looking for values of a,b and k # formula # mod <- nls(formula = var ~ a+b *(1-exp((-k)*t)), start=list(a=0, b=10,

...gt; > 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), exp(-exp(lrc) * x)), data = xy, : singular gradient", "1 error caught in start = list(lrc = lrc), algorithm = \"plinear\"): singular gradient")...

...-04 ,-4.574773e-04 , -2.368968e-03, -3.104634e-03, -5.833970e-03, -6.011945e-03, -7.737697e-03 , -8.203058e-03, -7.809603e-03, -6.623985e-03, -9.414477e-03) plot(slopes~quantiles) I want to fit two models: asymptotic decay and logistic decay(s-shaped). I tried self-starting functions (SSlogis and SSasymp) like this: dframe<-data.frame(cbind(slopes,quantiles)) names(dframe)<-c("slopes","quantiles") summary(mod1<-nls(slopes ~ SSlogis( quantiles, Asym, xmid, scal),data=dframe)) summary(mod1<-nls(slopes ~ SSasymp( quantiles, Asym, resp0, lrc),data=dframe)) and I trie...

...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), exp(-exp(lrc) * x)), data > = xy, : singular gradient", "1 error caught in start = list(lrc = lrc), algorithm = > \"plinear\"): singu...

...lly 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), exp(-exp(lrc) * x)), data >> = xy, : singular gradient", "1 error caught in start = list(lrc = lrc), algorithm = >> \"plinear\...

Hi to all, Is there a way we can fit a non linear model to a data using non linear least square method without necessarily initialising the parameters of the model. I find it hard to get the initial value of the parameter. Below is a sample of the code I have. *nachman<-nls(OARmedium$OCCUPANCY~1exp(-alpha*OARmedium$MEAN^beta),start=list(alpha=0.2,beta=0.1),data=OARmedium)summary(nachman)*

...;OK' (which should be 5 for the example). I'm using R version 1.9.1 on Windows XP. Thanks for any thoughts, Ken ################ library(nlme) data(Loblolly) maxIter <- c(1, 1, 1, 1, 1) returnObject <- c(FALSE, FALSE, FALSE, FALSE, TRUE) nlsList.Object <- nlsList(SSasymp, Loblolly) M1 <- function(maxIter, returnObject) { ok <- FALSE OK <- 0 while(ok==FALSE) { OK <- OK + 1 nlme.control.parms <- list("maxIter"=maxIter[OK], "returnObject"=returnObject[OK]) fm1 <- try(nlme(nlsList.Object, fixed = Asym...