similar to: ordering in 'gnls' with 'corCompSymm' corStruct

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]]

dear list, I am wondering if one can find examples and/or more detailed descriptions of modifications needed when going beyond standard corStruct classes (i.e. those already provided for use in lme/nlme)? When I looked at pages 238-239 of Pinheiro/Bates (2000): Mixed-effects models in S and S-plus, I found that I would need a bit more explicit guidance what to do for implementing a new

Dear List, After running a compound symmetric model using gls, I realized that the default contrasts were not the ones that made the most sense given the biological relationships among the factor levels. When I either changed the factor levels to re-arrange the order they occur in the gls model (not shown below) OR specifically change the contrasts I get the exact same estimates for the

>>>>> "VW" == Viechtbauer Wolfgang (STAT) <Wolfgang.Viechtbauer at STAT.unimaas.nl> >>>>> on Fri, 26 Sep 2008 18:00:19 +0200 writes: VW> Hi all, I'm trying to fit a marginal (longitudinal) VW> model with an exponential serial correlation function to VW> the Orange tree data set. However, R crashes frequently VW>

We are trying to use the corCompSymm function in nlme The example from the help pages for the corAR1 function gives the following > corAR1(0.2, form = ~ 1 | Mare) Correlation structure of class corAR1 representing Phi 0.2 We are expecting a somewhat similar correlation specification with the help page example for corCompSymm, but just get an error instead > corCompSymm(0.5, form = ~ 1 |

Dear R Friends, I need help with an error associated with corCompSymm in an lme fit. I am using a mixed effects model to analyze a split-plot with repeated measures and would like to fit with the compound symmetry correlation structure. This problem doesn't occur when using corAR1 or any of the other structures. I would greatly appreciate help on how to solve this issue. Here's my

Hi, I have confirmed temporal correlation problems in my data. Is there a possibility to use corCompSymm for a gamm()? I am an R-beginner. I have very short time series. There are three years and within each year, there are 10 weeks. he 10 weeks are the same every year and have not unique values, I seem not to be able to use AR-1 (I assume that I have too little data for autoregression

Dear R-helpers; While using gnls() to fit a function > Gbht0t.gnls <- gnls(h2 ~ Rht(b0, b1, b2, h1,t1, t2), data=gbht10, + params=list(b0 + b1 + b2 ~ Sisp -1), start=c(strssb0,strssb1,strssb2)) I encountered an error: "Error in model.frame(formula, rownames, variables, varnames, extras, extranames, : invalid variable type " Rht is a defined function to be

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've made a selfStart function for use with gnls and the following piece of code works nicely: check1 <- gnls(y ~ spot.shape.fct(xcord, ycord, background, spotintensity, rho, sigma, delta, mux, muy), start=getInitial(y ~ spot.shape.fct(xcord, ycord, background, spotintensity, rho,

Hi, I've been trying to work with the gnls() function in the "nlme" package. My decision to use gnls() was so that I could fit varPower and such to some of the data. However, in working with a small dataset, I've found that the results given by gnls() don't seem to make any sense and they differ substantially from those produced by nls(). I suspect that I am just

 Dear R-helpers, I'm a new R-user and I was trying to gain some experience with the GNLS function of the NLME package.  This is an extract from my dataset (it's a 432x6 data.frame) called "input", in the first column I have the values that I need to fit, while the remaining columns are input variables for the theoretical model, the function "mymodel" (which returns a

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

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

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

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

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

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 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:

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