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Research Report SRR95-014
On The Bias Of Bootstrap Model Selection Criteria
Kee-Won Lee
Abstract:
It is shown that a naive plug-in bootstrap model-selection criterion is
biased downwards
by an amount roughly equal to the number of parameters in the approximating
model. Bootstrap
methods are suggested for correcting the bias, and are shown theoretically
and numerically
to enjoy a high degree of accuracy. Comparison of the bootstrap method
with the asymptotic
method is made through an illustrative example.
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