© 1980 by Biometrika Trust
A note on the generalized information criterion for choice of a model
Department of Mathematics, Imperial College London
One way of selecting models is to choose that model for which the maximized log likelihood minus a multiple of the number of parameters estimated is a maximum. This note explores the choice of values for the multiplier, with the value one corresponding to Akaike's information criterion. The relationship with Bayesian procedures is mentioned.
Key Words: Discrimination between models Generalized AIO Generalized C
statistic Model choice criteria Posterior probabilities of models Simulation of linear models.
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