FUZZY LINEAR REGRESSION BASED ON LEAST ABSOLUTES DEVIATIONS

Authors

  • M. Kelkinnama Department of Mathematical Sciences, Isfahan University of Technology, Isfahan 84156-83111, Iran
  • S. M. Taheri Department of Mathematical Sciences, Isfahan University of Technology, Isfahan 84156-83111, Iran and Department of Statistics, School of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, Iran
Abstract:

This study is an investigation of fuzzy linear regression model for crisp/fuzzy input and fuzzy output data. A least absolutes deviations approach to construct such a model is developed by introducing and applying a new metric on the space of fuzzy numbers. The proposed approach, which can deal with both symmetric and non-symmetric fuzzy observations, is compared with several existing models by three goodness of t criteria. Three well-known data sets including two small data sets as well as a large data set are employed for such comparisons.

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Journal title

volume 9  issue 1

pages  121- 140

publication date 2012-02-11

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