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- W2792051238 abstract "An asymptotic expansion of the cross-validation criterion (CVC) using the Kullback-Leibler distance is derived when the leave-k-out method is used and when parameters are estimated by the weighted score method. By this expansion, the asymptotic bias of the Takeuchi information criterion (TIC) is derived as well as that of the CVC. Under canonical parametrization in the exponential family of distributions when maximum likelihood estimation is used, the magnitudes of the asymptotic biases of the Akaike information criterion (AIC) and CVC are shown to be smaller than that of the TIC. Examples in typical statistical distributions are shown." @default.
- W2792051238 created "2018-03-29" @default.
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- W2792051238 date "2018-03-09" @default.
- W2792051238 modified "2023-09-25" @default.
- W2792051238 title "Asymptotic biases of information and cross-validation criteria under canonical parametrization" @default.
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- W2792051238 doi "https://doi.org/10.1080/03610926.2017.1422759" @default.
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