On Testing of Fuzzy Hypothesis for Mean and Variance Using Centroid-Based New Distance Function Under Symmetric Fuzzy Environment

Authors

  • A Hari Ganesh Department of Mathematics, Poompuhar College, Affiliated to Bharathidasan University, Melaiyur, Nagapattinam (Dt), Tamilnadu, India
  • N Jaimaruthi Department of Mathematics, AnnaiVailankanni Arts and Science College, Affiliated to Bharathidasan University, Thanjavur, Tamilnadu India
  • R Ramesh Department of Mathematics, Arignar Anna Govt. Arts College, Affiliated to Bharathidasan University, Musiri, Tamilnadu India
  • M Seenivasan Mathematics wing, Directorate of Distance Education (DDE), Annamalai University, Annamalainagar, Tamilnadu India https://orcid.org/0000-0003-1475-923X

DOI:

https://doi.org/10.37256/cm.5120243317

Keywords:

testing of hypothesis, fuzzy data, fuzzy test statistics, distance function

Abstract

This paper discusses the problem of testing fuzzy and statistical hypotheses of the observed data are from a symmetric fuzzy environment. In this approach, many fuzzy tests statistics are obtained based on fuzzy data with varied forms of membership functions of fuzzy sets. To accept or reject the hypothesis of interest, a decision rule based on a new distance function to find the distance between symmetric fuzzy numbers with many forms of membership functions is proposed. The proposed method is employed to test hypotheses for mean and variance, as well as the difference between the means of a normal distribution and two normal distributions, with both known and unknown variances.

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Published

2023-12-26

How to Cite

1.
Ganesh AH, Jaimaruthi N, Ramesh R, Seenivasan M. On Testing of Fuzzy Hypothesis for Mean and Variance Using Centroid-Based New Distance Function Under Symmetric Fuzzy Environment. Contemp. Math. [Internet]. 2023 Dec. 26 [cited 2024 Feb. 27];5(1):60-92. Available from: https://ojs.wiserpub.com/index.php/CM/article/view/3317