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...ling factor. There are no extreme outliers in lat/lon. The model we try to fit is: > gamm3<-gamm(count~offset(offsetter)+s(lon,lat),random=list(code_tripnr=~1),family="poisson", niterPQL=200) Maximum number of PQL iterations: 200 iteration 1 iteration 2 Error in MEestimate(lmeSt, grps) : NA/NaN/Inf in foreign function call (arg 1) We tried several things. We added some noise to lon and lat, modelled the density instead of using a count with model offset, and we normalized the explanatory variables. We also changed several settings (see models below). Interestin...

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

...t 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 When I simply fit a gam model using the formula above, then it works ok. Is it possible to fit such a model with gamm? Thanks a lot! [[alternative HTML version deleted]]

...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) : Calloc could not allocate (65230 of 8) memory In addition: Warning message: Reached total allocation of 120Mb: see help(memory.size) I'm currently using a Win2000 machine with 128Mb RAM and a 1.2 Gb processor. My version of R is 1.7.1. Thanks in advance, Rodr...

...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 > testresult=lme(expr~visit,data=testdata,random=~visit|subject) I got the following error message. Error in MEestimate(lmeSt, grps) : Singularity in backsolve at level 0, block 1 In addition: There were 50 or more warnings (use warnings() to see the first 50) Could someone give me some hint on what went wrong? Thanks. Donglei Hu

...Error in Initialize.corCAR1(X[[2L]], ...) : Covariate must have unique values within groups for corCAR1 objects / I solved this by selecting one replicate but is there another solution for this? Moreover, when analyzing the data of one replicate, I received following error: /Error in MEestimate(lmeSt, grps) : Singularity in backsolve at level 0, block 1 / I have no idea how to solve this. It seems to be related with the complexity of the model because no error occurred when running a simpler gamm (gamm2): gamm2 <- gamm(richness~ s(Week,k=6,fx=FALSE) + factor(Treatment), correlation=corCAR...

...+s(x) ,data=DATA, random=~(1|Group)) I thus also tried to compare my model gm1, with another gm2 model of that sort: gm2<-gamm(Z~te(x,y)+te(x,y,by=Factor)+Factor,data=DATA,random=list(Group=~1)) but this type of models never converge and I obtain error messages of that sort: Error in MEestimate(lmeSt, grps) : Singularity in backsolve at level 0, block 1 2 questions from that: 1) Keeping in mind that my main question is to check whether tensor products smooths vary across factor levels, would the comparison of models gm and gm1 be sufficient for me? 2) Otherwise, is there something wrong in m...

...age + Sex, data = Orthodont, random = ~ 1) # Error in array(c(rep(1, p), .C(inner_perc_table, as.double(X), as.integer(unlist(grps)), : # object 'inner_perc_table' not found # #Upon debugging, this error is thrown with line 135 of lme.formula() code. # #fixDF <- getFixDF(X, grps, attr(lmeSt, "conLin")$dims$ngrps, lme(distance ~ age + Sex, data = Orthodont, random = ~ 1|Subject) # Error in array(c(rep(1, p), .C(inner_perc_table, as.double(X), as.integer(unlist(grps)), : # object 'inner_perc_table' not found gls(distance ~ age + Sex, data = Orthodont, correlati...

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 was not efficient and ran out of memory. If this is the reason, could you please help me improve my codes writing. However, as I slightly changed the parameters, it ran well. S...

...> names(aphids) [1] "site" "time" "shade" "treatp" "aphid" > library(nlme) > aphids<-groupedData(aphid~time|site/shade/treatp,data=aphids,outer=~shade*treatp) > model<-lme(aphid~shade*treatp,random=~time|site) Error in logLik.lmeStructInt(lmeSt, lmePars) : Calloc could not allocate (89359209 of 8) memory In addition: Warning message: Reached total allocation of 254Mb: see help(memory.size) *********************************************************** My response variable is number of aphids/colony on shaded cocoa tree...

...om = ~ 1) > > # Error in array(c(rep(1, p), .C(inner_perc_table, as.double(X), as.integer(unlist(grps)), : > # object 'inner_perc_table' not found > # > #Upon debugging, this error is thrown with line 135 of lme.formula() code. > # > #fixDF <- getFixDF(X, grps, attr(lmeSt, "conLin")$dims$ngrps, > > lme(distance ~ age + Sex, data = Orthodont, random = ~ 1|Subject) > > # Error in array(c(rep(1, p), .C(inner_perc_table, as.double(X), as.integer(unlist(grps)), : > # object 'inner_perc_table' not found > > gls(distance ~ age + Sex,...

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'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