search for: meem

I am trying to run a GLMM on some binomial data. My fixed factors include 2 dichotomous variables, day, and distance. When I run the model: modelA<-glmmPQL(Leaving~Trial*Day*Dist,random=~1|Indiv,family="binomial") I get the error: iteration 1 Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 >From looking at previous help topics,( http://tolstoy.newcastle.edu.au/R/help/02a/4473.html) I gather this is because of the dichotomous predictor variables - what approach should I take to avoid this pro...

...have 15 observations, each observation consisting of a reaction-time measure (RT) and an activation maesure (betadlpcv). since we want to analyze the influence of (age-)group and RT on the activation, we call: lme(betadlpcv ~ RT*group, data=our.data, random=~ RT |subject) this yields: Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 In addition: Warning message: Fewer observations than random effects in all level 1 groups in: lme.formula(betadlpcv ~ RT * group, data = patrizia.data, random = ~RT | what's the problem here? thanks for y...

...t;) Method Definition: function (x, ...) { print(x@.Data <mailto:x@.Data> , ...) } <environment: namespace:its> Signatures: x target "its" defined "its" > fundPME.lst[[1]]$irr An object of class "its" IRR HSBC MEEM 2005-10-31 0.1926175 0.07802736 Slot "dates": [1] "2005-10-31 Westeuropäische Normalzeit" > fundPME.lst[[1]]$irr@.Data IRR HSBC MEEM 2005-10-31 0.1926175 0.07802736 > print(fundPME.lst[[1]]$irr) IRR HSBC MEEM 2005-10-31 0.1926175...

...include four independent variables in the model everything is Ok, it works, but when I try to write a model with five independent variables like this: insmodel<-lme(briventral~sex*inslarge*temp*humid*wspeed,random=~1|site/pair,method="ML") I get this error message: Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 I haven't been able to find many people who usually work with mixed effects models, but apparently this problem is due to the fact that the model ?runs out? of degrees of freedom when including the fifth vari...

...,6),each=2),subj=factor(rep(1:16,each=2))) d$y <- rnorm(32) + rnorm(length(levels(d$subj)))[d$subj] anova(lme(y~x,random=~1|subj,data=d)) ## works anova(lme(y~as.factor(x),random=~1|subj,data=d)) ## works anova(lme(y~x+as.factor(x),random=~1|subj,data=d)) ## fails: # Error in MEEM(object, conLin, control$niterEM) : # Singularity in backsolve at level 0, block 1 summary(aov(y~x+as.factor(x)+Error(subj),data=d)) ## works: # Error: subj # Df Sum Sq Mean Sq F value Pr(>F) # x 1 8.434 8.434 4.780 0.0493 * # as.factor(x) 2 10.459 5.230 2....

...Lik-summary(fm2)$logLik) if (i==1 & j==2) results <- result if (i!=1 | j!=2) results <- rbind(results, result) } ----------------------------------------------------------------------------------------------------- after submitting this code, I got the error message saying "Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1", I know this might be some issue due to the missing values. what I want to do is to skip the 'bad' variable, for example, I got this error message when j=116, so I just wanna ignore variable116, is there...

...t is changed to: #!/usr/sbin/dtrace -s #pragma D option nspec=2 BEGIN { spec1 = speculation(); spec2 = speculation(); } END { commit(spec1); } END { commit(spec2); } ... then it compiles without issue. Is this restriction intentional? Thanks! -- meem

Dear R-ers, I am having trouble understanding why I am getting an error using glmmPQL (library MASS). I am getting the following error: iteration 1 Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 The long story: I have data from an experiment on pairwise comparisons between 3 treatments (a, b, c). So a typical run of an experiment involves a rater choosing between a versus b, b versus c, or a versus c...

Using OpenSolaris 2008.11 build 110. Created vnic''s and etherstub''s and they are displayed using dladm show-links but when the server is rebooted a ''dladm show-link'' is empty although the vnic and etherstub devices are still there and function properly. That is a real inconvenience, so why do the no longer show after a reboot or shutdown/start? Is there a

Hi all, I'm having some difficulty with lme. I am currently trying to run the following simple model anova(lme(x ~ f1 + f2 + f1:f2, data=m, random=~1|r1)) Which is currently producing the error Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 x is a numeric vector containing 194 observations. f1 is a factor vector containing two levels, and f2 is a different factor vector containing 5 different levels. R1 is a another factor vector containing 13 differe...

...2 10 1.48534 0.2724 nitro 3 45 37.68560 <.0001 Variety:nitro 6 45 0.30282 0.9322 # Excellent! However --- > fit2 <- lme(yield ~ Variety*nitro, random=~1|Block/Variety, subset= + !(Variety == "Golden Rain" & nitro == "0")) Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 -- ************************************************ * I.White * * University of Edinburgh * * Ashworth Laboratories, West Mains Road * * Edinburgh EH...

(Bcc''ed to networking discuss). Hi All, Have enclosed man page draft for dlstat(1M) herewith. This is part of the effort to gain better visibility into network traffic in light of crossbow features like virtual NICs, interrupt vs. polling modes etc. This in turn would greatly assist network performance analysis. It is also aimed at segregating link/flow configuration from

Hi, I am running Fedora 7 VM. On an earlier configuration with zaptel and Asterisk 1.4.21 , meetme worked alright. I upgraded to Dahdi and Asterisk 1.4.26, and the result is choppy sound via Meeme, while a simple Musiconhold works OK with descent audio quality. So I am sure its a Dahdi_dummy problem. Running dahdi_test gave me very poor results. Opened pseudo dahdi interface, measuring accuracy... 4.727% 4.725% 4.741% 4.903% 4.715% 4.459% 4.705% Doing a Top yields the folliwng results...

...a / (0.0083144*TEMP.K)) * exp(eps)) * time), data = Parameterg, fixed=list(A0+Ea~1,A1~Process), random=eps~1, start=c(93, 92, 34.5,37), control=list(msVerbose=TRUE, maxIter = 200), verbose=TRUE, method="REML", na.action=na.pass) this fit give the following error: Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 HOWEVER, in SAS the same model with covariate is WORKING! When I'm changing the fixed part in nmle as follows fixed=list(A0+Ea~1,A1~1|Process), then the following error is popping up: Error in contr.treatment...

...ames(data.E)<-c("id","Modality","logit","var.logit","dis","non.dis") data.bi<-rbind(data.S,data.E) require(nlme) lme(logit~dis*Modality+non.dis*Modality, random=~dis|id+non.dis| id,data=data.bi) but i recive a erro msg : Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 How in solve this problem? Whats is wrong? Thanks in advance -- Bernardo Rangel Tura, M.D,Ph.D National Institute of Cardiology Brazil

I decided to take a stab at 6601421 dladm set-linkprop should support multiple -p options along with some related linkprop fixes, but when I looked into dladm.c, was surprised to find that "dladm_parse_props()" is called from do_create_aggr and do_create_vlan in addition to the expected (by me, at least) do_create_vnic *linkprop functions. What happened here? Why do we pass in

...) # extreme wavelengths colnames(cmat.r) <- c(".L",".Q",".mid",".inter",".extr") contrasts(ordered(datamic$WA)<- cmat.r When I run the lme models, for all models involving WA, I get an error message (approximate English translation): Error in MEEM(object, conLin, control$niterEM) : Singularity encountered in inverse resolution in level 0, block 1 When I run the lmer models, for all models involving WA, I get an error message (approximate English translation): Warning message: In mer_finalize(ans) : gr cannot be computed at initial par (65...

...tic variation in the host plant is important, but "species" is of course a factor that structures genetic diversity. I thought the below model would be appropriate: > model<-lme(Nymphs~Species*Genotype,random=~1|Species/Genotype) ...but I then get the error message "Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1" I then tried to remove "Genotype" from the fixed factors, but then I get the error message "NaNs produced". > model<-lme(Nymphs~Species,random=~1|Species/Genotype) > summary(model) L...

...options(contrasts=c(factor="contr.treatment",ordered="contr.poly")); tmp$inter <- factor(tmp$inter); contrasts(tmp$inter) # perform multivariate analysis and test interaction effect m1 <- summary(lme(two~res1+res2+inter, random=~1|id, data=tmp)) ## Error in MEEM(object, conLin, control$niterEM) : ## Singularity in backsolve at level 0, block 1 Unfortunately, I have been unable to get it work. If I removed these two dummy variables like this: m2 <- summary(lme(two~inter, random=~1|id, data=tmp)) I did get some outputs, but these outp...

Author: meem Repository: /hg/zfs-crypto/gate Revision: 4d618a4110ff44c57939c29a3a8a198be2ec8352 Log message: 6336683 address::queue -v blows up kmdb and mdb 6338969 netstrategy needs to use SIOCGLIFFLAGS and friends to see IFF_VIRTUAL 6339847 ip_rcm incorrectly parses interface names 6340643 ip_rcm is lugging a...