similar to: How to increase iteration limit for lmer()?

Dear R users, I am building a hierarchical model on a large data set. It can take quite some time to finish one fit, I was just wondering whether it is possible to store the fit object (the result) to a file for later (offline) analysis. thanks Julia -- View this message in context: http://www.nabble.com/how-to-store-lme-lmer-fit-result-tp19910951p19910951.html Sent from the R help mailing

Hi, I am new to this list. I have a question regarding including both spatial and temporal random factors in lmer. These two are not nested, and an example of model I try to fit is model1<-lmer(Richness~Y+Canopy+Veg_cm+Treatment+(1|Site/Block/Plot)+(1|Year), family=poisson, REML=FALSE), where richness = integer Y & Treatment = factor Canopy & Veg_cm = numerical, continous

Hi, I have this message: Warning message: In mer_finalize(ans, verbose) : iteration limit reached without convergence (9) How to increase this limit? I try control=list(maxit=1000) I try maxIter and it dont work. Any idea Thanks Ronaldo -- Opportunities are usually disguised as hard work, so most people don't recognize them. -- > Prof. Ronaldo Reis J?nior | .''`.

Hi all, I have a problem when running lmer. In my data set, Agree is a binary(0/1) response. WalkerID and ObsID is the identification number of the subjects. the description of the other variables are as follows: > levels(regdat$Display) [1] "Dynamic" "Static" > levels(regdat$Survey) [1] "HM1_A" "HM1_B" "HM1_C" "HM2_A"

Hello, and sorry for asking a question without the data - hope it can still be answered: I've run two things on the same data: # Using lme: mix.lme <- lme(DV ~a+b+c+d+e+f+h+i, random = random = ~ e+f+h+i| group, data = mydata) # Using lmer mix.lmer <- lmer(DV ~a+b+c+d+(1|group)+(e|group)+(f|group)+(h|group)+(i|group), data = mydata) lme provided an output (fixed effects and random

Hey, I am having trouble with lmer. I am looking at the presence/absence of water shrews against habitat and other factors e.g so I used this: m1<-lmer(Presencebsence~Habitatype*Width+(1|Sitename))summary(m1) But i keep getting this error up Error in mer_finalize(ans) : Downdated X'X is not positive definite, 16.> summary(m1)Error in asMethod(object) : matrix is not symmetric [1,2] What

Hi dears while modeling an interaction random effect in lmer i receive the instantaneous error message > ldlM4<-lmer(ldl~rt*cd4+age+rf+pharmac+factor(hcv)+ + hivdur+(rt:cd4|id),na.action=na.omit,REML=F) *Warning message: In mer_finalize(ans) : false convergence (8) * I think the matter lies in syntax, 'cause i sistematically receive the same message even when changing response... PS:

Hello, I have a set of data that has a Date column looks like this: 12/9/2007 12/16/2007 1/1/2008 1/3/2008 1/12/2008 etc. I'd like the date to look something like the follow (so that I could sort by date easily). 20071209 20071216 20080101 20080103 20080112 How to do it? Thank you very much Julia -- View this message in context:

Hi, I was hoping to get some advice regarding the testing of interactions, when one factor is modelled as a random effect... I have a model with binomial error structure where the response variable is the proportion of time spent at the main sett (animals were tracked for 28 consecutive days in each season, and were recorded either at the main sett or an outlier sett, so the response variable is

Dear all, I'm attempting to use a piecewise regression to model the trajectory of reproductive traits with age in a longitudinal data set using a mixed model framework. The aim is to find three slopes and two points- the slope from low performance in early age to a point of high performance in middle age, the slope (may be 0) of the plateau from the start of high performance to the

Hi all, I am fairly new to mixed effects models and lmer, so bear with me. Here is a subset of my data, which includes a binary variable (lake (TOM or JAN)), one other fixed factor (Age) and a random factor (Year). lake FishID Age Increment Year 1 TOM 1 1 0.304 2007 2 TOM 1 2 0.148 2008 3 TOM 1 3 0.119 2009 4 TOM 1 4 0.053 2010 5

Dear R Community, I?m relatively new in the field of R and I hope someone of you can help me to solve my nerv-racking problem. For my Master thesis I collected some behavioral data of fish using acoustic telemetry. The aim of the study is to compare two different groups of fish (coded as 0 and 1 which should be the dependent variable) based on their swimming activity, habitat choice, etc.

Hello, I have a data file (.csv) that has a size of about 2.6 GB. I am not able to read in the whole data set because of the memory limit. I actually only need some columns (3 columns) of the data set, is there a way to read in specified columns? I am using windows. Thanks, Julia -- View this message in context:

Hello, I have a data set that looks like this. ID value 111 5 111 6 111 2 178 7 178 3 138 3 138 8 138 7 138 6 . . . I'd like to calculate the mean and var for each object identified by the ID. I can in theory just loop through the whole thing..., but is there a easier way/command which let me calculate the mean/var by ID? Thanks, Julia -- View this

Using lmer() on my data results in an error. The problem, I think, is my model specification. However, lm() works ok. I recreated this error with a more simple dataset. (See code below.) # word and letter recognition data # two within factors: # word length: 4, 5, 6 letters # letter position: 1-4 (in 4-letter words), 1-5 (in 5-letter words), 1-6 (in 6-letter words) # one dependent variable: #

Dear R community, I have two questions regarding fitting GLMM using maximum likelihood method. The first one arises from trying repeat an analysis in the Breslow and Clayton 1993 JASA paper. Model 3 of the epileptic dataset has two random effects, one subject specific, and one observation specific. Thus if we count random effects, there are more parameters than observations. When I try to run the

Dear R users, I need to compare two scatter plots, plot(x1, y1) plot(x2, y2) and would like to plot them in the same figure. How do I do it? Thank you. -- View this message in context: http://www.nabble.com/two-scatter-plots-in-one-tp21963375p21963375.html Sent from the R help mailing list archive at Nabble.com.

Hello, I have a vector: x <- c("A", "A", "A", "B", "A", "A", "C") I'd like to compare each of elements of vector x from its previous element (except for the 1st element which does not have previous element). So I'd like to get a vector y (of same length) that looks something like (0, 0, 0, 1, 1, 0, 1) or (F, F, F,

Dear R users, I am running lmer() and having memory problem: "reached total allocation of 1535Mb". The lmer() function was successful (no errors or warnings). However when I do "summary(fit.lmer), I got this "Error: cannot allocate vector of size 19.5 Mb). I used memory.size() and got 1880. I used memory.limit(2500) to increase the memory size to 2500Mb, however I still get

Hello, I have been attempting to run a poisson glmm using lme4 for some time now and have had a lot of trouble. I would say 9 times out of 10 I receive the following warning: CHOLMOD warning: %h Error in mer_finalize(ans) : Cholmod error `not positive definite' at file:../Cholesky/t_cholmod_rowfac.c, line 432 My data are counts of microbe colony forming units (CFUs) collected from