A corrected AIC for the selection of seemingly unrelated regressions models

Details A corrected AIC for the selection of seemingly unrelated regressions models A corrected AIC for the selection of seemingly unrelated regressions models

2009-06-03

arxiv.org/abs/0906.0708v2

Statistics

Methodology

9 pages including 1 figure and 3 tables; v2: revtex4, typos corrected

Scientific paper

A bias correction to Akaike's information criterion (AIC) is derived for
seemingly unrelated regressions models. The correction is of particular use
when the sample size is not much larger than the number of fitted parameters. A
small-sample simulation study indicates that the bias-corrected AIC (AICc)
provides better model choices than other model selection criteria.

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