How can I apply the AIC criterion to time series data using MATLAB?

As part of the Econometrics Toolbox, how can i apply the AIC criterion to time series data using MATLAB.

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Is there any way without using GARCH functions such as garchfit. If the only way to AIC is to apply GARCH functions, what is meant by number of parameters??

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Eventhough I am not familiar with GARCH models, here's an example of how to use AIC/BIC for model selection (based on examples in the documentation):

load Data_MarkPound
dem2gbp = price2ret(Data);

%# fit model with specification parameters spec1
spec1 = garchset('P',1, 'Q',1, 'Display','off');
[coeff1,errors1,LLF1] = garchfit(spec1, dem2gbp);
numParams1 = garchcount(coeff1);
%#garchdisp(coeff1,errors1)

%# fit model with specification parameters spec2
spec2 = garchset('P',2, 'Q',1, 'Display','off');
[coeff2,errors2,LLF2] = garchfit(spec2, dem2gbp);
numParams2 = garchcount(coeff2);
%#garchdisp(coeff2,errors2)

%# find the best model with the smallest AIC/BIC
numObsv = length(dem2gbp);
[AIC1,BIC1] = aicbic(LLF1, numParams1, numObsv)
[AIC2,BIC2] = aicbic(LLF2, numParams2, numObsv)