[R-sig-ME] default optimizer in lmer 1.1-7?
Ben Bolker
bbolker at gmail.com
Thu Nov 6 17:11:33 CET 2014
[cc'ing to r-sig-mixed-models]
You can see the default optimizer for GLMMs by running
> glmerControl()$optimizer
[1] "bobyqa" "Nelder_Mead"
This means that bobyqa is used for the first (nAGQ=0) stage of
optimization, whereas Nelder-Mead is used for the second (nAGQ>0). If
optimizer is a length-1 vector, the same optimizer is used for both stages
of optimization (I *think* this is explained in the documentation, but it
might not be ...)
If you read the NEWS file <
http://cran.r-project.org/web/packages/lme4/news.html> slightly more
carefully, you'll see that the default was only changed for `lmer` fits,
not `glmer` fits -- from 1.1-4,
* The default optimizer for lmer fits has been switched from "Nelder_Mead"
to "bobyqa" because we have generally found the latter to be more reliable.
To switch back to the old behaviour, use
control=lmerControl(optimizer="Nelder_Mead").
We are very seriously considering making bobyqa, or nloptwrap, the
default for GLMMs as well (for both stages of optimization) in the next
release.
I haven't looked at your results in too much detail otherwise -- it's a
little bit puzzling that all the AICs seem to be about the same, but I was
in a hurry (and I want to send this off before the problem gets buried in
my inbox).
On Thu, Nov 6, 2014 at 10:16 AM, Jordi Moya Laraño <jordi at eeza.csic.es>
wrote:
> Dear Ben,
> We have been going crazy about replicating previous analyses with glmer
> and I think that what may be happening is that when you copiled the last
> version you left in unadvertedly "Nelder_Mead" by default instead of
> "bobyqa" as it is claimed to be done in the last version of the manual. Is
> that a possibility? My analyses give the results by default as those
> obtained if you were using "Nelder_Mead". I am also wondering whether
> Nelder_Mead results should be trusted whatsoever.
>
> Here are my codes and results (the results using "bobyqa" are the once
> qualitatively very similar to those using previous versions of lme4):
> >
> TELA_MANIP1<-glmer(ABUNDANCE~RAIN*TRAT+(1|SITE)+(1|caso),data=tela2013,poisson)
> > summary(TELA_MANIP1)
> Generalized linear mixed model fit by maximum likelihood (Laplace
> Approximation) ['glmerMod']
> Family: poisson ( log )
> Formula: ABUNDANCE ~ RAIN * TRAT + (1 | SITE) + (1 | caso)
> Data: tela2013
>
> AIC BIC logLik deviance df.resid
> 265.8 282.2 -124.9 249.8 49
>
> Scaled residuals:
> Min 1Q Median 3Q Max
> -1.67352 -0.56382 0.04347 0.63915 1.61069
>
> Random effects:
> Groups Name Variance Std.Dev.
> caso (Intercept) 0.0815360 0.28555
> SITE (Intercept) 0.0001355 0.01164
> Number of obs: 57, groups: caso, 57; SITE, 7
>
> Fixed effects:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) 1.515432 0.004537 334.0 < 2e-16 ***
> RAINLOW 0.013886 0.004533 3.1 0.00219 **
> TRATNO_PREDATORS -0.621030 0.004532 -137.0 < 2e-16 ***
> TRATPREDATORS 0.238772 0.004534 52.7 < 2e-16 ***
> RAINLOW:TRATNO_PREDATORS -0.251747 0.004531 -55.6 < 2e-16 ***
> RAINLOW:TRATPREDATORS 0.046884 0.004532 10.3 < 2e-16 ***
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> Correlation of Fixed Effects:
> (Intr) RAINLOW TRATNO TRATPR RAINLOW:TRATN
> RAINLOW 0.000
> TRATNO_PRED 0.000 0.000
> TRATPREDATO 0.000 0.000 0.001
> RAINLOW:TRATN 0.000 0.000 0.000 0.000
> RAINLOW:TRATP 0.000 0.000 0.001 0.000 0.000
> > library(car)
> > Anova(TELA_MANIP1,type="III",test="Chisq")
> Analysis of Deviance Table (Type III Wald chisquare tests)
>
> Response: ABUNDANCE
> Chisq Df Pr(>Chisq)
> (Intercept) 1.1158e+05 1 < 2e-16 ***
> RAIN 9.3829e+00 1 0.00219 **
> TRAT 2.1559e+04 2 < 2e-16 ***
> RAIN:TRAT 3.1937e+03 2 < 2e-16 ***
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
>
> >
> TELA_MANIP1<-glmer(ABUNDANCE~RAIN*TRAT+(1|SITE)+(1|caso),data=tela2013,poisson,glmerControl(optimizer
> = c("bobyqa")))
> > summary(TELA_MANIP1)
> Generalized linear mixed model fit by maximum likelihood (Laplace
> Approximation) ['glmerMod']
> Family: poisson ( log )
> Formula: ABUNDANCE ~ RAIN * TRAT + (1 | SITE) + (1 | caso)
> Data: tela2013
> Control: glmerControl(optimizer = c("bobyqa"))
>
> AIC BIC logLik deviance df.resid
> 265.8 282.2 -124.9 249.8 49
>
> Scaled residuals:
> Min 1Q Median 3Q Max
> -1.67891 -0.56610 0.04277 0.63769 1.61159
>
> Random effects:
> Groups Name Variance Std.Dev.
> caso (Intercept) 0.08089 0.2844
> SITE (Intercept) 0.00000 0.0000
> Number of obs: 57, groups: caso, 57; SITE, 7
>
> Fixed effects:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) 1.51734 0.19288 7.867 3.64e-15 ***
> RAINLOW 0.01200 0.30771 0.039 0.9689
> TRATNO_PREDATORS -0.62228 0.27051 -2.300 0.0214 *
> TRATPREDATORS 0.23893 0.23320 1.025 0.3056
> RAINLOW:TRATNO_PREDATORS -0.24897 0.46286 -0.538 0.5907
> RAINLOW:TRATPREDATORS 0.04942 0.36944 0.134 0.8936
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> Correlation of Fixed Effects:
> (Intr) RAINLOW TRATNO TRATPR RAINLOW:TRATN
> RAINLOW -0.617
> TRATNO_PRED -0.703 0.440
> TRATPREDATO -0.817 0.510 0.581
> RAINLOW:TRATN 0.410 -0.665 -0.584 -0.339
> RAINLOW:TRATP 0.519 -0.833 -0.367 -0.632 0.554
> > library(car)
> > Anova(TELA_MANIP1,type="III",test="Chisq")
> Analysis of Deviance Table (Type III Wald chisquare tests)
>
> Response: ABUNDANCE
> Chisq Df Pr(>Chisq)
> (Intercept) 61.8859 1 3.639e-15 ***
> RAIN 0.0015 1 0.968899
> TRAT 13.6932 2 0.001063 **
> RAIN:TRAT 0.5580 2 0.756552
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> >
> >
> >
> TELA_MANIP1<-glmer(ABUNDANCE~RAIN*TRAT+(1|SITE)+(1|caso),data=tela2013,poisson,glmerControl(optimizer
> = c("Nelder_Mead")))
> > summary(TELA_MANIP1)
> Generalized linear mixed model fit by maximum likelihood (Laplace
> Approximation) ['glmerMod']
> Family: poisson ( log )
> Formula: ABUNDANCE ~ RAIN * TRAT + (1 | SITE) + (1 | caso)
> Data: tela2013
> Control: glmerControl(optimizer = c("Nelder_Mead"))
>
> AIC BIC logLik deviance df.resid
> 265.8 282.2 -124.9 249.8 49
>
> Scaled residuals:
> Min 1Q Median 3Q Max
> -1.67425 -0.55993 0.04442 0.63968 1.61151
>
> Random effects:
> Groups Name Variance Std.Dev.
> caso (Intercept) 8.144e-02 0.285378
> SITE (Intercept) 6.202e-05 0.007875
> Number of obs: 57, groups: caso, 57; SITE, 7
>
> Fixed effects:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) 1.512854 0.004555 332.1 < 2e-16 ***
> RAINLOW 0.016625 0.004551 3.7 0.000259 ***
> TRATNO_PREDATORS -0.619082 0.004550 -136.1 < 2e-16 ***
> TRATPREDATORS 0.243134 0.004552 53.4 < 2e-16 ***
> RAINLOW:TRATNO_PREDATORS -0.254128 0.004549 -55.9 < 2e-16 ***
> RAINLOW:TRATPREDATORS 0.042442 0.004551 9.3 < 2e-16 ***
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> Correlation of Fixed Effects:
> (Intr) RAINLOW TRATNO TRATPR RAINLOW:TRATN
> RAINLOW 0.000
> TRATNO_PRED 0.000 0.000
> TRATPREDATO 0.000 0.000 0.001
> RAINLOW:TRATN 0.000 0.000 0.000 0.000
> RAINLOW:TRATP 0.000 0.000 0.001 0.000 0.000
> > library(car)
> > Anova(TELA_MANIP1,type="III",test="Chisq")
> Analysis of Deviance Table (Type III Wald chisquare tests)
>
> Response: ABUNDANCE
> Chisq Df Pr(>Chisq)
> (Intercept) 110319.413 1 < 2.2e-16 ***
> RAIN 13.343 1 0.0002594 ***
> TRAT 21372.929 2 < 2.2e-16 ***
> RAIN:TRAT 3207.377 2 < 2.2e-16 ***
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
>
> >
> TELA_MANIP1<-glmer(ABUNDANCE~RAIN*TRAT+(1|SITE)+(1|caso),data=tela2013,poisson,glmerControl(optimizer
> = c("Nelder_Mead")))
> > summary(TELA_MANIP1)
>
> Generalized linear mixed model fit by maximum likelihood (Laplace
> Approximation) ['glmerMod']
> Family: poisson ( log )
> Formula: ABUNDANCE ~ RAIN * TRAT + (1 | SITE) + (1 | caso)
> Data: tela2013
> Control: glmerControl(optimizer = c("Nelder_Mead"))
>
> AIC BIC logLik deviance df.resid
> 265.8 282.2 -124.9 249.8 49
>
> Scaled residuals:
> Min 1Q Median 3Q Max
> -1.67425 -0.55993 0.04442 0.63968 1.61151
>
> Random effects:
> Groups Name Variance Std.Dev.
> caso (Intercept) 8.144e-02 0.285378
> SITE (Intercept) 6.202e-05 0.007875
> Number of obs: 57, groups: caso, 57; SITE, 7
>
> Fixed effects:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) 1.512854 0.004555 332.1 < 2e-16 ***
> RAINLOW 0.016625 0.004551 3.7 0.000259 ***
> TRATNO_PREDATORS -0.619082 0.004550 -136.1 < 2e-16 ***
> TRATPREDATORS 0.243134 0.004552 53.4 < 2e-16 ***
> RAINLOW:TRATNO_PREDATORS -0.254128 0.004549 -55.9 < 2e-16 ***
> RAINLOW:TRATPREDATORS 0.042442 0.004551 9.3 < 2e-16 ***
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> Correlation of Fixed Effects:
> (Intr) RAINLOW TRATNO TRATPR RAINLOW:TRATN
> RAINLOW 0.000
> TRATNO_PRED 0.000 0.000
> TRATPREDATO 0.000 0.000 0.001
> RAINLOW:TRATN 0.000 0.000 0.000 0.000
> RAINLOW:TRATP 0.000 0.000 0.001 0.000 0.000
> > library(car)
> > Anova(TELA_MANIP1,type="III",test="Chisq")
> Analysis of Deviance Table (Type III Wald chisquare tests)
>
> Response: ABUNDANCE
> Chisq Df Pr(>Chisq)
> (Intercept) 110319.413 1 < 2.2e-16 ***
> RAIN 13.343 1 0.0002594 ***
> TRAT 21372.929 2 < 2.2e-16 ***
> RAIN:TRAT 3207.377 2 < 2.2e-16 ***
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
>
> best wishes,
> Jordi
>
> Jordi Moya-Laraño
> Functional and Evolutionary Ecology
> Estación Experimental de Zonas Áridas - CSIC
> Carretera de Sacramento s/n
> La Cañada de San Urbano
> 04120-Almería
> Spain
>
> phone:+34 950281045 ext. 419
> email: jordi at eeza.csic.es
> www.eeza.csic.es/foodweb
>
>
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