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Fuzzy Statistics

  • James J. Buckley

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 149)

Table of contents

  1. Front Matter
    Pages i-xi
  2. James J. Buckley
    Pages 1-4
  3. James J. Buckley
    Pages 5-16
  4. James J. Buckley
    Pages 17-22
  5. James J. Buckley
    Pages 23-26
  6. James J. Buckley
    Pages 27-30
  7. James J. Buckley
    Pages 31-36
  8. James J. Buckley
    Pages 37-38
  9. James J. Buckley
    Pages 39-42
  10. James J. Buckley
    Pages 43-45
  11. James J. Buckley
    Pages 47-48
  12. James J. Buckley
    Pages 49-52
  13. James J. Buckley
    Pages 53-59
  14. James J. Buckley
    Pages 61-67
  15. James J. Buckley
    Pages 69-72
  16. James J. Buckley
    Pages 73-76
  17. James J. Buckley
    Pages 77-79
  18. James J. Buckley
    Pages 81-90
  19. James J. Buckley
    Pages 91-93
  20. James J. Buckley
    Pages 95-98
  21. James J. Buckley
    Pages 99-102
  22. James J. Buckley
    Pages 103-106
  23. James J. Buckley
    Pages 107-111
  24. James J. Buckley
    Pages 113-116
  25. James J. Buckley
    Pages 117-121
  26. James J. Buckley
    Pages 123-128
  27. James J. Buckley
    Pages 129-132
  28. James J. Buckley
    Pages 133-137
  29. James J. Buckley
    Pages 139-141
  30. James J. Buckley
    Pages 143-155
  31. Back Matter
    Pages 157-167

About this book

Introduction

This monograph introduces elementary fuzzy statistics based on crisp (non-fuzzy) data. In the introductory chapters the book presents a very readable survey of fuzzy sets including fuzzy arithmetic and fuzzy functions. The book develops fuzzy estimation and demonstrates the construction of fuzzy estimators for various important and special cases of variance, mean and distribution functions. It is shown how to use fuzzy estimators in hypothesis testing and regression, which leads to a comprehensive presentation of fuzzy hypothesis testing and fuzzy regression as well as fuzzy prediction.

Keywords

Estimator Maple Multiple Regression Regression construction fuzzy fuzzy set linear regression sets statistics

Authors and affiliations

  • James J. Buckley
    • 1
  1. 1.Mathematics DepartmentUniversity of Alabama at BirminghamBirminghamUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-39919-3
  • Copyright Information Springer-Verlag Berlin Heidelberg 2004
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-05924-7
  • Online ISBN 978-3-540-39919-3
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site