Akaike's 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 F-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 F-test to estimate the number of classes of sites. © 1986, The Japanese Pharmacological Society. All rights reserved.
CITATION STYLE
Kamikubo, K., Murase, H., Murayama, M., & Miura, K. (1986). Microcomputer-Based Nonlinear Regression Analysis of Ligand-Binding Data: Application of Akaike’s Information Criterion. The Japanese Journal of Pharmacology, 40(2), 342–346. https://doi.org/10.1254/jjp.40.342
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