[R-sig-ME] how to extract the BIC value

[Gabor Grothendieck]

Another possibility would be for AIC methods to define AIC(,.., k =
"BIC") or AIC(..., method = "BIC").

This would not require any change to stats but to encourage
standardization it would be best if stats did define this for existing
AIC methods in stats.

On Mon, May 17, 2010 at 9:45 AM, Gabor Grothendieck
<ggrothendieck at gmail.com> wrote:
> BIC seems like something that would logically go into stats in the
> core of R, as AIC is already, and then various packages could define
> methods for it.
>
> On Mon, May 17, 2010 at 9:29 AM, Douglas Bates <bates at stat.wisc.edu> wrote:
>> On Mon, May 17, 2010 at 5:54 AM, Andy Fugard (Work)
>> <andy.fugard at sbg.ac.at> wrote:
>>> Greetings,
>>>
>>> Assuming you're using lmer, here's an example which does what you need:
>>>
>>>> (fm1    <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy))
>>> Linear mixed model fit by REML
>>> Formula: Reaction ~ Days + (Days | Subject)
>>>   Data: sleepstudy
>>>  AIC  BIC logLik deviance REMLdev
>>>  1756 1775 -871.8     1752    1744
>>> Random effects:
>>>  Groups   Name        Variance Std.Dev. Corr
>>>  Subject  (Intercept) 612.092  24.7405
>>>          Days         35.072   5.9221  0.066
>>>  Residual             654.941  25.5918
>>> Number of obs: 180, groups: Subject, 18
>>>
>>> Fixed effects:
>>>            Estimate Std. Error t value
>>> (Intercept)  251.405      6.825   36.84
>>> Days          10.467      1.546    6.77
>>>
>>> Correlation of Fixed Effects:
>>>     (Intr)
>>> Days -0.138
>>>
>>>> (fm1fit <- summary(fm1)@AICtab)
>>>      AIC      BIC    logLik deviance  REMLdev
>>>  1755.628 1774.786 -871.8141 1751.986 1743.628
>>>
>>>> fm1fit$BIC
>>> [1] 1774.786
>>
>> That's one way of doing it but it relies on a particular
>> representation of the object returned by summary, and that is subject
>> to change.
>>
>> I had thought that it would work to use
>>
>> BIC(logLik(fm1))
>>
>> but that doesn't because the BIC function is imported from the nlme
>> package but not later exported.  The situation is rather tricky - at
>> one point I defined a generic for BIC in the lme4 package but that led
>> to conflicts when multiple packages defined different versions.  The
>> order in which the packages were loaded became important in
>> determining which version was used.
>>
>> We agreed to use the generic from the nlme package, which is what is
>> now done.  However, I don't want to make the entire nlme package
>> visible when you have loaded lme4 because of resulting conflicts.
>>
>> I can get the result as
>>
>>> (fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy))
>> Linear mixed model fit by REML
>> Formula: Reaction ~ Days + (Days | Subject)
>>   Data: sleepstudy
>>  AIC  BIC logLik deviance REMLdev
>>  1756 1775 -871.8     1752    1744
>> Random effects:
>>  Groups   Name        Variance Std.Dev. Corr
>>  Subject  (Intercept) 612.090  24.7405
>>          Days         35.072   5.9221  0.066
>>  Residual             654.941  25.5918
>> Number of obs: 180, groups: Subject, 18
>>
>> Fixed effects:
>>            Estimate Std. Error t value
>> (Intercept)  251.405      6.825   36.84
>> Days          10.467      1.546    6.77
>>
>> Correlation of Fixed Effects:
>>     (Intr)
>> Days -0.138
>>> nlme:::BIC(logLik(fm1))
>>    REML
>> 1774.786
>>
>> but that is unintuitive.  I am not sure what the best approach is.
>> Perhaps Martin (or anyone else who knows namespace intricacies) can
>> suggest something.
>>
>>
>>> Tahira Jamil wrote:
>>>> Hi
>>>> I can extract the AIC value of a model like this
>>>>
>>>> AIC(logLik(fm0)
>>>>
>>>> How can I extract the BIC value if I need!
>>>>
>>>> Cheers
>>>> Tahira
>>>> Biometris
>>>> Wageningen University
>>>>
>>>> _______________________________________________
>>>> R-sig-mixed-models at r-project.org mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>>
>>>
>>> --
>>> Andy Fugard, Postdoctoral researcher, ESF LogICCC project
>>> "Modeling human inference within the framework of probability logic"
>>> Department of Psychology, University of Salzburg, Austria
>>> http://www.andyfugard.info
>>>
>>> _______________________________________________
>>> R-sig-mixed-models at r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>>
>>
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>>
>