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  • 标题:Robust Regression Analysis with LR-Type Fuzzy Input Variables and Fuzzy Output Variable
  • 本地全文:下载
  • 作者:Dan Zhang ; Qiujun Lu
  • 期刊名称:Journal of Data Analysis and Information Processing
  • 印刷版ISSN:2327-7211
  • 电子版ISSN:2327-7203
  • 出版年度:2016
  • 卷号:04
  • 期号:02
  • 页码:64-80
  • DOI:10.4236/jdaip.2016.42006
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要:In this paper, we propose a fuzzy linear regression model with LR-type fuzzy input variables and fuzzy output variable, the fuzzy extent of which may be different. Then we give the iterative solution of the proposed model based on the Weighted Least Squares estimation procedure. Some properties of the estimates are proved. We also define suitable goodness of fit index and its adjusted version useful to evaluate the performances of the proposed model. Based on the Least Median Squares-Weighted Least Squares (LMS-WLS) estimation procedure, we give robust estimation steps for the proposed model. Compared with the well-known fuzzy Least Squares method, the effectiveness of our model on reducing the outliers influence is shown by using two examples.
  • 关键词:LR-Type Fuzzy Input Variables;LR-Type Fuzzy Output Variable;LMS-WLS;Outliers;Robust
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