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An adjusted network information criterion for model selection in statistical neural network models
In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC) criterion, based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The ANIC improves model...
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2016
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| LEADER | 00000njm a2000000a 4500 | ||
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| 001 | oai:repository.ui.edu.ng:123456789/5337 | ||
| 042 | |a dc | ||
| 720 | |a Udomboso, C. G. |e author | ||
| 720 | |a Amahia, G. N. |e author | ||
| 720 | |a Dontwi, I. K. |e author | ||
| 260 | |c 2016 | ||
| 520 | |a In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC) criterion, based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The ANIC improves model selection in more sample sizes than does the NIC. | ||
| 024 | 8 | |a 1538-9472 | |
| 024 | 8 | |a ui_art_udomboso_adjusted_2016 | |
| 024 | 8 | |a Journal of Modern Applied Statistical Methods 15(2), pp. 411-427 | |
| 024 | 8 | |a http://ir.library.ui.edu.ng/handle/123456789/5337 | |
| 653 | |a Statistical neural network | ||
| 653 | |a Network information criterion | ||
| 653 | |a Network information criterion | ||
| 653 | |a Adjusted network information criterion | ||
| 653 | |a Transfer function | ||
| 245 | 0 | 0 | |a An adjusted network information criterion for model selection in statistical neural network models |