[R] Obtaining fitted model information

John Fox jfox at mcmaster.ca
Mon Nov 1 14:47:23 CET 2004

```Dear Renaud,

Thanks -- I forgot about the error variance!

John

--------------------------------
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario
905-525-9140x23604
http://socserv.mcmaster.ca/jfox
--------------------------------

> -----Original Message-----
> From: Renaud Lancelot [mailto:renaud.lancelot at cirad.fr]
> Sent: Sunday, October 31, 2004 2:07 PM
> To: John Fox
> Cc: Thomas.Volscho at uconn.edu; r-help at stat.math.ethz.ch
> Subject: Re: [R] Obtaining fitted model information
>
> With models estimated with lm, the number of parameters is
> obtained adding 1 to the rank of the fitted model (to account
> for the residuals variance). The number of parameters is
> found in logLik objects:
>
>  > # example from ?lm
>  > ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
>  > trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
>  > group <- gl(2,10,20, labels=c("Ctl","Trt"))  > weight <-
> c(ctl, trt)  > lm.D9 <- lm(weight ~ group)  >  > # rank of
> the model  > lm.D9\$rank [1] 2  >  > # loglik  > logLik(lm.D9)
> `log Lik.' -20.08824 (df=3)  >  > # number of parameters in
> the model  > attr(logLik(lm.D9), "df") [1] 3  >  > # AIC  >
> AIC(lm.D9) [1] 46.17648  >  > c(- 2 * logLik(lm.D9) + 2 *
> attr(logLik(lm.D9), "df")) [1] 46.17648  >  > # AICc = AIC +
> 2 * k * (k + 1)/(n - k - 1)  >  > AICc_lm <- function(x){
> +   n <- length(resid(x))
> +   k <- attr(logLik(lm.D9), "df")
> +   AIC(x) + 2 * k * (k + 1) / (n - k - 1)
> +   }
>  >
>  > AICc_lm(lm.D9)
> [1] 47.67648
>
> Best regards,
>
> Renaud
>
>
> John Fox a Ã©crit :
>
> > Dear Thomas,
> >
> > To get the number of independent parameters in the lm
> object mod, you
> > can use mod\$rank, sum(!is.na(coef(mod)), or -- if there are
> no linear
> > dependencies among the columns of the model matrix --
> length(coef(mod)).
> >
> > I hope this helps,
> >  John
> >
> > --------------------------------
> > John Fox
> > Department of Sociology
> > McMaster University
> > Hamilton, Ontario
> > 905-525-9140x23604
> > http://socserv.mcmaster.ca/jfox
> > --------------------------------
> >
> >
> >>-----Original Message-----
> >>From: r-help-bounces at stat.math.ethz.ch
> >>[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Thomas W
> >>Volscho
> >>Sent: Sunday, October 31, 2004 12:41 PM
> >>To: r-help at stat.math.ethz.ch
> >>Subject: [R] Obtaining fitted model information
> >>
> >>Dear list,
> >>I am brand new to R  and using Dalgaard's (2002) book Introductory
> >>Statistics with R (thus, some of my terminology may be incorrect).
> >>
> >>I am fitting regression models and I want to use Hurvich and Tsai's
> >>AICC statistic to examine my regression models.  This
> penalty can be
> >>expressed as: 2*npar * (n/(n-npar-1)).
> >>
> >>While you can obtain AIC, BIC, and logLik, I want to impose
> the AICC
> >>
> >>After fitting a model.  Is there a way of obtaining the "npar" and
> >>then assigning it to a variable?
> >>
> >>Essentially, I want to then write a simple function to add the AICC
> >>penalty to (-2*logLik).
> >>
> >>Thank you in advance for any help,
> >>Tom Volscho
> >>
> >>************************************
> >>Thomas W. Volscho
> >>Dept. of Sociology U-2068
> >>University of Connecticut
> >>Storrs, CT 06269
> >>Phone: (860) 486-3882
> >>http://vm.uconn.edu/~twv00001
> >>
> >>______________________________________________
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> >>https://stat.ethz.ch/mailman/listinfo/r-help
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> >
> >
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