The statistical inferences of fuzzy regression based on bootstrap techniques

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• 作者：Woo-Joo Lee (1)
  Hye Young Jung (1)
  Jin Hee Yoon (2)
  Seung Hoe Choi (3)
  
  1. Department of Mathematics ; Yonsei University ; Seoul ; Republic of Korea
  2. School of Mathematics and Statistics ; Sejong University ; Seoul ; Republic of Korea
  3. School of Liberal Arts and Science ; Korea Aerospace University ; Goyang ; Republic of Korea
  
• 关键词：Fuzzy regression ; Fuzzy least squares method ; Bootstrap method
• 刊名：Soft Computing - A Fusion of Foundations, Methodologies and Applications
• 出版年：2015
• 出版时间：April 2015
• 年：2015
• 卷：19
• 期：4
• 页码：883-890
• 全文大小：871 KB
• 参考文献：1. Akbari, MG, Mohammadalizadeh, R, Rezaei, M (2012) Bootstrap statistical inference about the regression coefficients based on fuzzy data. Int J Fuzzy Syst 14: pp. 549-556
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• 刊物类别：Engineering
• 刊物主题：Numerical and Computational Methods in Engineering
  Theory of Computation
  Computing Methodologies
  Mathematical Logic and Foundations
  Control Engineering
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1433-7479

文摘

In this paper, we estimate the parameters of fuzzy regression models and investigate a statistical inferences with crisp inputs and fuzzy outputs for each \(\alpha \) -cut. The proposed approaches of statistical inferences are fuzzy least squares (FLS) method and bootstrap technique. FLS is constructed on the basis of minimizing the sum of square of the total difference between observed and estimated outputs. Numerical examples are illustrated to perform the hypotheses test and to provide the percentile confidence regions by proposed approach.