singular convergence with lmer()
It converged for me for lme4_0.999999-0. Estimates look different from what you posted at the site. Reinhold Kliegl
dat$Part <- factor(dat$Part) ( fit <- lmer(y ~ (1|Operator)+(1|Part)+(1|Part:Operator), data=dat) )
Linear mixed model fit by REML
Formula: y ~ (1 | Operator) + (1 | Part) + (1 | Part:Operator)
Data: dat
AIC BIC logLik deviance REMLdev
-619.7 -603.4 314.9 -630.3 -629.7
Random effects:
Groups Name Variance Std.Dev.
Part:Operator (Intercept) 0.00081854 0.028610
Part (Intercept) 1.06721729 1.033062
Operator (Intercept) 0.00031226 0.017671
Residual 0.00063295 0.025159
Number of obs: 192, groups: Part:Operator, 96; Part, 12; Operator, 8
Fixed effects:
Estimate Std. Error t value
(Intercept) 2.7171 0.2983 9.109
On Sun, Jul 8, 2012 at 9:58 PM, Ben Bolker <bbolker at gmail.com> wrote:
laurent stephane <laurent_step at ...> writes:
Dear all, Using the latest CRAN version of lme4 I get the following warning from lmer() : Warning message: In mer_finalize(ans) : singular convergence (7)
My model is not complicated and it works fine with SAS (if you are interested in the details of my model see forums.cirad.fr/logiciel-R/viewtopic.php?t=5071 )
What argument could I change in lmer() to overcome this warning ?
This warning emerges from the nlminb optimizer used in the guts of lme4, and I don't think there's much you can do to suppress it or change the behavior of nlminb to avoid it. The best you could do would be to use other packages (SAS, other versions of lme4 or nlme, etc.) to see if the correct answer was achieved despite the warning. Ben Bolker
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