Skip to main content
SpringerLink
Log in

Some maximum likelihood estimators for the fuzzy linear model

  • Fuzzy Sets And Possibility Theory
  • Conference paper
  • First Online:
Uncertainty and Intelligent Systems (IPMU 1988)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 313))

  • 145 Accesses

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. A. Celmins, Least squares model fitting to fuzzy linear data, Fuzzy Sets and Systems 22 (1987), 245–269.

    Google Scholar 

  2. A. Celmins, Multidimensional least squares fitting of fuzzy models, Mathematical Modelling (1988), to appear.

    Google Scholar 

  3. P. Diamond, Fuzzy least squares, Information Sciences (1988), to appear.

    Google Scholar 

  4. P. Diamond, Least squares fitting of several fuzzy variables, Proc. Second IFSA Congress, Tokyo, July 20–25 Vol.I (1987), 329–332.

    Google Scholar 

  5. P. Diamond, Fuzzy kriging, (1987), submitted for publication.

    Google Scholar 

  6. D. Dubois and H. Prade, “Fuzzy Sets and Systems: Theory and Applications,” Academic Press, New York, 1980.

    Google Scholar 

  7. B. Heshmaty and A. Kandel, Fuzzy linear regression and its applications to forecasting in uncertain environment, Fuzzy Sets and Systems 15 (1985), 159–191.

    Google Scholar 

  8. E. P. Klement, M. L. Puri and D. A. Ralescu, Limit theorems for fuzzy random variables, Proc. R. Soc. Lond. A 407 (1986), 171–182.

    Google Scholar 

  9. N. N. Lyashenko, Statistics of random compacts, J. Soviet Math. 21 (1983), 76–92.

    Google Scholar 

  10. M. L. Puri and D. A. Ralescu, Fuzzy random variables, J. Math. Anal. Applus. 114 (1986), 409–422.

    Google Scholar 

  11. E. Schlechtman and G. Schlechtman, Estimating the parameters in regression with uniformly distributed errors, J. Statist. Comput. Simul. 26 (1986), 269–281.

    Google Scholar 

  12. H. Tanaka, S. Uejima and K. Asai, Linear regression analysis with fuzzy model, IEEE Trans. Syst. Man, Cybern. SMC-12 (1982), 903–907.

    Google Scholar 

  13. A. W. Tucker, Dual systems of homogeneous linear relations, Linear Inequalities and Related Systems, Annals of Mathematics Study, Princeton University No. 38 (1956), 3–17.

    Google Scholar 

  14. A. Kaufman and M. M. Gupta, “Introduction to Fuzzy Arithmetic,” Van Nostrand Reinhold, New York, 1985.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Mathematics Department, University of Queensland, 4067, St. Lucia, Australia

    Phil Diamond

Authors
  1. Phil Diamond
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

B. Bouchon L. Saitta R. R. Yager

Rights and permissions

Reprints and permissions

Copyright information

© 1988 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Diamond, P. (1988). Some maximum likelihood estimators for the fuzzy linear model. In: Bouchon, B., Saitta, L., Yager, R.R. (eds) Uncertainty and Intelligent Systems. IPMU 1988. Lecture Notes in Computer Science, vol 313. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-19402-9_58

Download citation

  • DOI: https://doi.org/10.1007/3-540-19402-9_58

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-19402-6

  • Online ISBN: 978-3-540-39255-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation