Olivier,

type ?AIC and have a look at the description

Description:

     Generic function calculating the Akaike information criterion for
     one or several fitted model objects for which a log-likelihood
     value can be obtained, according to the formula -2*log-likelihood
     + k*npar, where npar represents the number of parameters in the
     fitted model, and k = 2 for the usual AIC, or k = log(n) (n the
     number of observations) for the so-called BIC or SBC (Schwarz's
     Bayesian criterion).

AIC = -2*log-likelihood + k*npar can be negative as SBC, too.

Hannu

On 9/7/07, Olivier MARTIN <olivier.martin@avignon.inra.fr> wrote:
>
> Hi all,
>
>
> I obtained negative values for AIC and BIC criteria for a particular
> model that I have
> developped...
>
> I don't remember to have negative values for these crietria for others
> applications, so I am a
> little suprised... Could anyone tell me if something is wrong or his
> conclusion concerning my model?
>
> Best regards,
> Olivier.
>
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