Of course it is possible. Please consider the following texample with artificial data:

<hansl>
nulldata 500
setobs 1 1 --special-time-series
genr time

set seed 20140413 # For reproduction
series wn = randgen(n,0,1)

# Stationary ARMA(2,2) model
series z = 4.5
z = 1 + 0.25*z(-1) + 0.55*z(-2) + wn + 0.5*wn(-1) + 0.5*wn(-2)

# Visual eyecandy, can be omitted
# gnuplot z time --with-lines --output=display
#corrgm z 24 --plot=display

matrix AICs = zeros(6,6)
matrix BICs = zeros(6,6)
loop i=1..6 --quiet
    loop j=1..6 --quiet
        arima $i 0 $j ; z
        AICs[$i,$j]=$aic
        BICs[$i,$j]=$bic
    endloop
endloop

mwrite(AICs,"AICs.csv")
mwrite(BICs,"BICs.csv")

</hansl>

What it does: varies the $p$ and $q$ parameters of ARIMA(p,d,q) estimation and generates two matrices with the criteria. Just delete the first line from the .csv files and use your favourite means of visualisation (e.g. Excel2LaTeX) for comparison. A beautiful way of doing that via a heatmap is described here: http://texblog.org/2013/06/13/latex-heatmap-using-tabular/ You may want to transform the table for easier interpretation (e.g. subtract the second smallest value from all and take logs if the order of variance is too high, like 371.1 371.2 371.7 370.8 410.4 456.9).

Please see the final result on page 9 of this document: https://www.dropbox.com/s/g7vf0per3pp45r3/avr-sem.pdf (it is in Russian, except for the Universal Language of Mathematics).

You may also want to perform Poskitt—Tremayne test in order to determine whether to include a model or not.

Is that what you wanted?

--
Yours sincerely, | С уважением,
Andreï V. Kostyrka. | Андрей Викторович Костырка.
http://kostyrka.ru, http://kostyrka.ru/blog

2014-04-26 4:51 GMT+04:00 Tim Nall <tnall.ling@gmail.com>:

All,

Please forgive my simple questions. For ARIMA modelling, using the ACF
and PACF to determine the pdq parameters requires subjective judgment
based on experience. Answers are seldom clear-cut. As the subject
header says, can a somewhat more objective path be found in quickly
running through ARIMA models, varying parameters, acquiring AIC, BIC,
HQC, and comparing? I don't think the time-series-->VAR lag selection
option gets at precisely the same thing. Thank you TMN
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