search for: meestimate

...nd sub sampling 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). Inte...

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 > So R says they don't exist, although summary(AnNlmeObject) works fine. What's going o...

...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 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]]

...------------------------------- > nlme(Count ~ quad.PBMC.model(aL, aN, T0), + data = tissueData, + weights = varConstPower(form =~ Count), + start = list( fixed = c(rep(1000, 8), -2, -2) ), + fixed = list(T0 ~ TypeTissue-1, aL ~ 1, aN ~ 1), + random = aL + aN ~ 1|Tissue + ) Error in MEestimate(nlmeSt, grpShrunk) : Singularity in backsolve at level 0, block 1 > > --------------------------------------------- The above command clearly this doesn't work, but if I comment out the "weights = ..." line, it executes with no problem. I'd greatly appreciate any guidan...

...4 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 > 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

...me time: /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=...

...m4(Z~factor+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 wron...

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 we...

...ty 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 "Error in MEestimate(nlmeSt, grpShrunk) : Singularity in backsolve at level 0, block 1\n" be returned rather than only an error message being returned? Setting the "returnObject" nlme control option to TRUE seems to return an nlme object only when the maximum number of iterations is reached without meet...

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