similar to: convergence problem gamm / lme

Hi All, I've been having a little trouble with creating a loop that will run a a series of t.tests for inspection, Below is the code i've tried, and some checks i've looked at. I've used the get(paste()) idea as i was told previously that the use of the eval should try and be avoided. I've run a single syntax to check that my systax is correct and works without any problems

Hi all, I would like to fit a gamm model of the form: Y~X+X*f(z) Where f is the smooth function and With random effects on X and on the intercept. So, I try to write it like this: gam.lme<- gamm(Y~ s(z, by=X) +X, random=list(groups=pdDiag(~1+X)) ) but I get the error message : Error in MEestimate(lmeSt, grps) : Singularity in backsolve at level 0, block 1

Hi, I have a dataset like this, > testdata Grouped Data: expr ~ visit | subject expr visit subject 1 6.502782 V1 A 2 6.354506 V1 B 3 6.349184 V1 C 4 6.386301 V2 A 5 6.376405 V2 B 6 6.758640 V2 C 7 6.414142 V3 A 8 6.354521 V3 B 9 6.396636 V3 C I tried the command >

Dear all, I?m analyzing this dataset containing biodiversity indices, measured over time (Week), and at various contaminant concentrations (Treatment). We have two replicates (Replicate) per treatment. I?m looking for the effects of time (Week) and contaminant concentration (Treatment) on diversity indices (e.g. richness). Initial analysis with GAM models showed temporal autocorrelation of

Hi list, I'm working with gamm models of this sort, using Simon Wood's mgcv library: gm<- gamm(Z~te(x,y),data=DATA,random=list(Group=~1)) gm1<-gamm(Z~te(x,y,by=Factor)+Factor,data=DATA,random=list(Group=~1)) with a dataset of about 70000 rows and 110 levels for Group in order to test whether tensor product smooths vary across factor levels. I was wondering if comparing those two

Dear R-users, I am a dentist (so forgive me if my question looks stupid) and came across a problem when I did simulations to compare a few single level and two level regressions. The simulations were interrupted and an error message came out like 'Error in MEestimate(lmeSt, grps) : Singularity in backsolve at level 0, block 1'. My collegue suggested that this might be due to my codes

Greetings all The help file for GAMM in mgcv indicates that the log likelihood for a GAMM reported using summary(my.gamm$lme) (as an example) is not correct. However, in a past R-help post (included below), there is some indication that the likelihood ratio test in anova.lme(mygamm$lme, mygamm1$lme) is valid. How can I tell if anova.lme results are meaningful (are AIC, BIC, and logLik

Hi, I'm trying to work out how the nlme function estimates the variances of the fixed effects parameters, so I tried to look at the code for these functions: summary.nlme, summary.lme, MEestimate. > MEestimate Error: Object "MEestimate" not found > summary.nlme Error: Object "summary.nlme" not found > summary.lme Error: Object "summary.lme" not found

lme() and gls() models from the nlme package are all crashing with R.3.4.0. Identical code ran correctly, without error in R 3.3.3 and earlier versions. The behavior is easily demonstrated using one of the examples form the lme() help file, along with two simple variants. I have commented the errors generated by these calls, as well as the lines of code generating them, in the code example below.

Dear R community, I'm fitting a complex mixed-effects model that requires numerous iterations and function evaluations. I note that nlminb accepts a list of control parameters, including eval.max. Is there a way to change the default eval.max value for nlminb when it is being called from lme? Thanks for any thoughts, Andrew -- Andrew Robinson Department of Mathematics and Statistics

Hi all R users ! I'm using gamm function from Simon Wood's mgcv package, to fit a spatial regression Generalized Additive Mixed Model, as covariates I have the geographical longitude and latitude locations of indexed data. I include a random effect for each district (dist) so the code is fit <- gamm(y~s(lon,lat,bs="tp", m=2)+offset(log(exp.)), random=list(dist=~1),

Dear All Hopefully someone out there can point out what I am missing! I have a (large, several hundred) dataset of gardens in which over two years the presence/absence of a particular bird species is noted each week. I have good reason to believe there is a difference between the two years in the weekly proportion of gardens and would like to assess this, before going on to look in more detail at

Hello, Excuse me for posting two questions in one day, but I figured it would be better to ask my questions in separate emails. I will again give the caveat that I'm not a statistician by training, but have a fairly decent understanding of probability and likelihood. As before, I'm trying to fit a nonlinear model to a dataset which has two main factors using nlme. Within the dataset

Dear all, I've stumbled a similar issue with the package cluster when compiling the 3.4.0 version with the settings of Fedora RPM specs. Compiling R with the default setting of configure yields a version that works for cluster... and nlme. I did not find the exact option that was the cause of this issue but I'm willing to help. Erwan PS: This is the reason why R is

Hi there, My question is about the 'theta' parameter in specification of a NB GAMM. I have fit a GAM with an optimum structure of: SB.gam4<-gam(count~offset(vol_offset)+ s(Depth_m, by=StnF, bs="cs")+StageF*RegionF, family=negbin(1, link=log), data=Zoop_2011[Zoop_2011$SpeciesF=='SB',]) However, this GAM shows heterogeneity in the

Hi dear R-listers, I'm trying to fit a 3-level model using lme in R. My sample size is about 2965 and 3 factors: year (5 levels), ssize (4 levels), condition (2 levels). When I issue the following command: > lme(var~year*ssize*condition,random=~ssize+condition|subject,data=smp,method ="ML") I got the following error: Error in logLik.lmeStructInt(lmeSt, lmePars) :

Hi everyone. I'm working with nlme and I have a question regarding nlme fits that fail because of singularity issues. Specifically, there a way to return an nlme object when the estimation process runs into a singular matrix? For example, can the results up to the point of an error such as "Error in solve.default(pdMatrix(a, fact = TRUE)) : system is computationally singular" or

Dear group, I tried to run a Repeated Mesures Anova for Mixed effects model and I got a warnning after entering the model specification saying: "Reached total allocation of 254Mb: see help(memory.size)". here is part of the log: *********************************************************** > aphids<-read.table("aphid.txt",header=T) > attach(aphids) > names(aphids)

Dear R-users, I did some more research and I'm still not sure how to set up an ANCOVA with nestedness. Specifically I'm not sure how to express chicks nested within boxes. I will be getting Pinheiro & Bates (Mixed Effects Models in S and S-Plus) but it will not arrive for another two weeks from our interlibrary loan. The goal is to determine if there are urbanization (purban)

Hi all, I am currently playing around with Sins of a Solar Empire 1.05, usually I simply start the game in compiz, which works more or less good. I now tried the game without compiz, but the result was kind of strange. The screen remains black in the upper third. It is as iff there is some kind of offsett that is used to raw the graphics. And it is raqlly only the prahics of the game, the mouse