search for: pqlmaxit

...,# ditto msMaxIter = 200, ## msTol = sqrt(.Machine$double.eps), ## FIXME: should be able to pass tolerances to nlminb() msVerbose = getOption("verbose"), niterEM = 15, EMverbose = getOption("verbose"), PQLmaxIt = 30,# FIXME: unused; PQL currently uses 'maxIter' instead gradient = TRUE, Hessian = FALSE # unused _FIXME_ ) { list(maxIter = as.integer(maxIter), tolerance = as.double(tolerance), msMaxIter = as.integer(msMaxIter), ## msTol...

...odal. As far as I understood, I have to use a model with random intercepts and slopes, because the observations within each plant are not independent. So far so good ========(lme4)========= glmm1<-GLMM(count~thick+I(thick^2),random=~thick+I(thick^2) |plantid,poisson,data=Dataset,control=list(PQLmaxIt=10000)) > summary(glmm1) Generalized Linear Mixed Model Family: poisson family with log link Fixed: lixt ~ thick + I(thick^2) Data: Dataset AIC BIC logLik -125.2406 -83.7346 72.62031 Random effects: Groups Name Variance Std.Dev. Corr plantid (Intercept) 0....

...RData is last.warning, thus: > last.warning $"optim or nlminb returned message false convergence (8)" "LMEoptimize<-"(`*tmp*`, value = list(maxIter = 200, tolerance = 1.49011611938477e-08, msMaxIter = 200, msVerbose = 0, niterEM = 15, EMverbose = FALSE, PQLmaxIt = 30, analyticGradient = TRUE, analyticHessian = FALSE)) This was generated by a call, in a previous session,to lmer() There may be a problem with the package Matrix, but it seems a bit extreme that this prevents restoration of the session. John Maindonald john.maindonald at anu.edu.au --please...

...in: LMEopt(x = mer, value = cv) 2: nlminb returned message false convergence (8) in: LMEopt(x = mer, value = cv) 3: nlminb returned message false convergence (8) in: LMEopt(x = mer, value = cv) I tried to increase maximum iteration limit by adding control=list(msMaxIter=600, maxIter=300, PQLmaxIt=100) That seems not help. What can I do next? Thanks all! Mingyu Feng ================================================================================ Department of Computer Science Tutoring Research Group Worcester Polytechnic Institute

Dear list members, In re-running with GLMM() from the lme4 package a generalized-linear mixed model that I had previously fit with glmmPQL() from MASS, I'm getting a warning of a convergence failure, even when I set the method argument of GLMM() to "PQL": > bang.mod.1 <- glmmPQL(contraception ~ as.factor(children) + cage + urban, + random=~as.factor(children) + cage +

I'll address two issues. The first is today's error message and the other is change management for contributed packages on CRAN. TODAY'S ERROR MESSAGE I switched from the 0.995-1 versions of lme4 and Matrix to those referenced in the subject line this afternoon. Prior to using these packages on anything else, I applied them to code that 'worked' (provided numerical results

I use lmer to fit a mixed effect model.It give some warnings.what does this warnings mean? and what should I do? > (fm2.mlm <- lmer(qd ~ edu + jiankang + peixun +hunyin + cadcj + age + age2 + sex + dangyuan + Comp.1 + Comp.2+trust.cz1 +(trust.cz1|commid), data = individual,na.action = "na.exclude",family="quasibinomial")) Generalized linear mixed model fit using PQL