similar to: seg.fault from nlme::gnls() {was "[R-sig-ME] GNLS Crash"}

Dear all, How can I extract the total and residual d.f. from a gnls object? I have tried str(summary(gnls.model)) and str(gnls.model) as well as gnls(), but couldn?t find the entry in the resulting lists. Many thanks! Best wishes Christoph -- Dr. rer.nat. Christoph Scherber University of Goettingen DNPW, Agroecology Waldweg 26 D-37073 Goettingen Germany phone +49 (0)551 39 8807 fax +49

This works fine: fit42<-nls(Vfs~SSlogis(Months,Asym.Int+Asym.Group*Groupdum,xmid,scal), data=df, start=c(Asym.Int=22,Asym.Group=5,xmid=2,scal=6), na.action=na.omit) But this, identical except using gnls, doesn't converge: fit43<-gnls(Vfs~SSlogis(Months,Asym.Int+Asym.Group*Groupdum,xmid,scal), data=df, start=c(Asym.Int=22,Asym.Group=5,xmid=2,scal=6), na.action=na.omit) Error in gnls(Vfs

Hi, I am not sure this is a bug but I can repeat it, The functions and data are below. I know this is nasty data, and it is very questionable whether a 4pl model is appropriate, but it is data fed to an automated tool and I would have hoped for an error. Does this repeat for anyone else? My details: > version _ platform i686-pc-linux-gnu

Back on January 16, a message on R-help from Ravi Varadhan described a problem with gnls using weights=varPower(). The problem was that the fit failed with error Error in eval(expr, envir, enclos) : Object "." not found I can reliably get this error in version 2.0.1-patched 2004-12-09 on Windows XP and 2.0.1-Patched 2005-01-26 on Linux. The key feature of that example is that the

Hi I use gnls to fit non linear models of the form y = alpha * x**beta (alpha and beta being linear functions of a 2nd regressor z i.e. alpha=a1+a2*z and beta=b1+b2*z) with variance function varPower(fitted(.)) which sounds correct for the data set I use. My purpose is to use the fitted models for predictions with other sets of regressors x, z than those used in fitting. I therefore need to

Hi all, I'm trying to fit a nonlinear (logistic-like) regression, and I'd like to get some recommendations for which package to use. The expression I want to fit is something like: y ~ A * exp(X * Beta1) / (1 + exp(-(x + X * Beta2 - xmid)/scal)) Basically, it's a logistic function, but I want to be able to modify the saturation amplitude by a few parameters (Beta1) and shift the

Hi R-users, Could you give me some advice in solving the problem of such error message from gnls and nls? ## begin error message "Problem in gnls(y1 ~ glogit4(b, c, m, t, x), data.frame(x..: Step halving factor reduced below minimum in NLS step " ##and "Problem in nls(y ~ 1/(1 + exp((xmid - x)/scal)), data = x..: step factor reduced below minimum "? Thank you in

I have been using gnls with the weights argument (and varConstPower) to specify a variance structure for curve fits. In attempting to extract the parameters for the variance model I am seeing results I don't understand. When I simply display the model (or use "summary" on the model), I get what seem like reasonable values for both "power" and "const". When I

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

Hello list: How to extract the value of "Rho" from a gnls() object. I am using gnls() function similar to res <- gnls(y~SSmicmen(),correlation=corCompSymm(form~1|b),data=dat) Thanks in advance, Mahbub. -- Mahbub Latif School of Mathematical Sciences Queen Mary, University of London United Kingdom [[alternative HTML version deleted]]

I have been using the nls function to fit some simple non-linear regression models for properties of graphite bricks to historical datasets. I have then been using these fits to obtain mean predictions for the properties of the bricks a short time into the future. I have also been calculating approximate prediction intervals. The information I have suggests that the assumption of a normal

Last week (Wed 9/10/2003, "regression questions") I posted a question regarding the use of gnls( ) and its dissimilarity to the syntax that nls( ) will accept. No one replied, so I partly answered my own question by constructing indicator variables for use in gnls( ). The code I used to construct the indicators is at the end of this email. I do have a nagging, unanswered

Hi: I have data from an assay in the form of two vectors, one is response and the other is a predictor. When I attempt to fit a 5 parameter logistic model with "nls", I get converged parameter estimates. I also get the same answers with "gnls" without specifying the "weights" argument. However, when I attempt to use the "gnls" function and try to

Hi all, I'm working with a dataset from 10 treatments, each treatment with 30 subjects, each subject measured 5 times. The plot of the dataset suggests that a 3-parameter logistic could be a reasonable function to describe the data. When I try to fit the model using gnls I got the message 'Step halving factor reduced below minimum in NLS step'. I´m using as the initial values of the

Hi All, I have question about speficifying a constant in gnls() from package nlme. Here is a testing code: ############# library(nlme) x = exp( rnorm(100)) y = 1/(1+x) + rnorm(100)/10 plot( y ~ x) fm1 = gnls( y ~ 1/(1+(x/v)^w), start=list( v=1, w=1)) a =1; b=1; fm2 = gnls( y ~ a/(b+(x/v)^w), start=list( v=1, w=1)) #This won't work because I don't know to set $a$ and $b$ as

Dear R-list members, Some months ago I wrote a message on the usage of gnls (nlme library) and here I come again. Let me give an example: I have a 10 year length-at-age data set of 10 fishes (see growth.dat at the end of this message) and I want to fit a von Bertalanffy growth model, Li= Linf*(1-exp(-k*(ti-t0))) where Li = length at age i, Linf= asymptotic length, k= curvature parameter, ti=

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

Dear R users; I was trying to fit a nonlinear model using gnls (nlme version 3.1-80, R 2.5.0, WinXP) and I got the following error and warning message: Error in gnls(ht ~ a1 * hd * (1 - a2 * exp(-a3 * (dbh/dq2))), data = hdat, : Step halving factor reduced below minimum in NLS step In addition: Warning message: $ operator is deprecated for atomic vectors, returning NULL in:

Dear R users; I'm trying to fit nonlinear model (asymptotic regression model) with gnls from library nlme in R 2.1.0 with no big issues so far. However after installed the version R 2.1.1, when I tried to update the initial model including a var-cov model I've got the error: "Error: Object "convIter" not found". This error occurs only with R 2.1.1. Any ideas? Thanks

Dear Xen users! In case you were struggling with recent version of th gplpv drivers, I''ve possibly found an LVM related bug in it, and reported to James Harper. Thats''s the point: I''ve tested the mentioned version of your driver on top of 32bit xen-3.2.1 32bit xen-3.3.0 and 64bit xen xen-3.3.0 hypervisors, dom0 was always an appropriate version of a 32bit PAE kernel,