Bias and variance reduction techniques for bootstrap information criteria |
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Authors: | Genshiro Kitagawa Sadanori Konishi |
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Institution: | 1.The Institute of Statistical Mathematics,Tokyo,Japan;2.Faculty of Mathematics,Kyushu University,Fukuoka,Japan |
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Abstract: | We discuss the problem of constructing information criteria by applying the bootstrap methods. Various bias and variance reduction
methods are presented for improving the bootstrap bias correction term in computing the bootstrap information criterion. The
properties of these methods are investigated both in theoretical and numerical aspects, for which we use a statistical functional
approach. It is shown that the bootstrap method automatically achieves the second-order bias correction if the bias of the
first-order bias correction term is properly removed. We also show that the variance associated with bootstrapping can be
considerably reduced for various model estimation procedures without any analytical argument. Monte Carlo experiments are
conducted to investigate the performance of the bootstrap bias and variance reduction techniques. |
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Keywords: | |
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