Proceedings of the Fuzzy System Symposium
26th Fuzzy System Symposium
Session ID : MG2-3
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AIC for Model Selection of Normal Distribution by Fuzzy Interval Data
*Mikihiko Konishi, Tetsuji Okuda
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Abstract
We have proposed the processing methods for the fuzzy interval data which including vagueness of observer. And the usefulness of these methods are investigated. In these methods, to consider the vagueness of observed data, the correction value is added to the result which is obtained by normal statistical method using the representative values of fuzzy interval data. And as a application method, we have proposed the processing method in model selection by AIC. But, in this proposed method, the correction value is calculated by using the process of maximum likelihood estimation. That is, the proposed method dose not correct AIC directly. So, in this research, we consider the effectiveness of direct correction value in AIC. And the effectiveness of this method is discussed in the model selection of normal distribution.
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© 2010 Japan Society for Fuzzy Theory and Intelligent Informatics
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