  We consider the problem of constructing an adaptive bridge regression
modeling, which is a penalized procedure by imposing different weights to
different coefficients in the bridge penalty term. A crucial issue in the
modeling process is the choices of adjusted parameters included in the models.
We treat the selection of the adjusted parameters as model selection and
evaluation problems. In order to select the parameters, model selection
criteria are derived from information-theoretic and Bayesian approach. We
conduct some numerical studies to investigate the effectiveness of our proposed
modeling strategy.
