Re: model selection problem
- From: "Vadim Pliner" <Vadim.Pliner@xxxxxxxxxxxxxxxxxxx>
- Date: 14 Jul 2005 10:51:27 -0700
Carsten Steinhoff wrote:
> Hello experts,
>
> I want to select the "optimal" distribution from a set of "assumable"
> models. The selection criterion will be AIC or BIC which is based on the
> empirical LogLik. Now my problem:
>
> I've made experiments with the Log-Gamma-Distribution. This DF in some
> cases could be best fit for my problem. But - as I think due to the
> log(x) as input - the LogLik for this function is very very small
> compared with the LogLik of other DFs fitted to the same dataset (e.g.
> Weibull, Lognormal etc). Following a LogLik derived criterion the
> LG-Distr should be best fitting in EVERY case. Graphics show me that it
> does sometimes, but other times does not.
>
> Where is the error, or how could I make the Log-Gamma compareable to the
> others?
>
> Thanks for any hint.
>
> Carsten
>
> P.S.: The LG is the only DF that is not ready-made in my stat-Software
> (R). And so I use DFgamma(log(x)) to "generate" it.
Carsten,
Log Likelihood incorporates probabilities rather than actual values of
x or log(x). Therefore, I cannot see a reason why the Log Likelihood
would get smaller or higher just because you take log of x.
HTH,
Vadim Pliner
.
- References:
- model selection problem
- From: Carsten Steinhoff
- model selection problem
- Prev by Date: Re: r-Squared Question
- Next by Date: Re: model selection problem
- Previous by thread: model selection problem
- Next by thread: Re: model selection problem
- Index(es):
Relevant Pages
|
