Microcomputer-Based Nonlinear Regression Analysis of Ligand-Binding Data: Application of Akaikes Information Criterion
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概要
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Akaikes information criterion (AIC) (Akaike, H., IEEE Trans. Automat. Contr. AC-19, 716-723 (1974)) was applied to estimate statistically the number of classes of binding sites from ligand-binding data. Several sets of data were analyzed by both the AIC method and the <I>F</I>-test method. Good agreement was obtained between results from both methods. The present results suggest that the AIC method can be a good alternative to the <I>F</I>-test to estimate the number of classes of sites.
著者
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MIURA Kiyoshi
The Third Department of Internal Medicine, Gifu University School of Medicine
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MURASE Hiroshi
The Third Department of Internal Medicine, Gifu University School of Medicine
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KAMIKUBO Keita
The Third Department of Internal Medicine, Gifu University School of Medicine
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MURAYAMA Masanori
The Third Department of Internal Medicine, Gifu University School of Medicine
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