[R-sig-ME] singular convergence with lmer()

[Reinhold Kliegl]

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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