[R] Calculation of BIC done by leaps-package
Peter Ehlers
ehlers at ucalgary.ca
Mon Dec 27 19:22:19 CET 2010
On 2010-12-26 06:47, Jan Henckens wrote:
> Hi Folks,
>
> I've got a question concerning the calculation of the Schwarz-Criterion
> (BIC) done by summary.regsubsets() of the leaps-package:
>
> Using regsubsets() to perform subset-selection I receive an regsubsets
> object that can be summarized by summary.regsubsets(). After this
> operation the resulting summary contains a vector of BIC-values
> representing models of size i=1,...,K.
>
> My problem is that I can't reproduce the calculation of these BIC
> values. I already tried to use extractAIC(...,k=log(n)),
> AIC(...,k=log(n)) and manual calculation using the RSS-vector but none
> matches the calculation done by the summary-function. I already checked
> for constants that could be the reason for the differences but i found
> out, that the values vary apart of adding a constant term.
>
>
> The source code of the leaps-package states the package calculates the
> BIC this way:
>
> bicvec<-c(bicvec,(n1+ll$intercept)*log(vr)+i*log(n1+ll$intercept))
>
> with:
>
> ## number of observations - Intercept:
> n1<-ll$nn-ll$intercept
> ## fraction of sum of squared residulas model i
> ## and sum of squared residuals null model, I
> ## just can't understand why the vector ll$ress
> ## is subscripted double
ll$ress is a one-column matrix
> vr<-ll$ress[i,j]/ll$nullrss
> ## maximum number of variables
> i
>
> ^^ This seems to match the calculation done by extractAIC but it doesn't!
>
> Maybe anyone can tell me about the reason of the variation of the
> BIC-values?
>
> Best regards,
> Jan Henckens
>
>
>
> ### Minimal Example:
> require(leaps)
> bridge<-
> read.table("http://www.stat.tamu.edu/~sheather/book/docs/datasets/bridge.txt",
> header=TRUE)
> fmla.full<- formula(Time ~ .)
> (lm.model<- summary(regsubsets(fmla.full,data=bridge,weights=NULL,
> intercept=TRUE, method="forward")))
> lm.model$bic
> ### The first two models constructed via lm():
> extractAIC(lm(Time~Dwgs,data=bridge),k=log(nrow(bridge)))
> extractAIC(lm(Time~Dwgs+Case,data=bridge),k=log(nrow(bridge)))
>
> or see
>
> http://www.henckens.de/min_example.R
>
Does this help:
bic1 <- extractAIC(lm(Time~Dwgs,data=bridge),k=log(nrow(bridge)))
bic2 <- extractAIC(lm(Time~Dwgs+Spans,data=bridge),k=log(nrow(bridge)))
## NOTE: predictors are 'Dwgs' and 'Spans', not 'Dwgs' and 'Case'.
all.equal(bic2[2] - bic1[2], diff(lm.model$bic)[1])
#[1] TRUE
## or
bic0.1 <- lm.model$bic[1]
bic0.2 <- lm.model$bic[2]
bic1 - bic0.1
#[1] 410.4472
bic2 - bic0.2
#[1] 410.4472
## So, the values do differ from extractAIC by a constant.
BTW: You probably want to omit 'Case'; I doubt that it's an
intended predictor.
Peter Ehlers
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