Intuitionistic Fuzzy Hypothesis Testing with Fuzzy Data

ATALIK G., Senturk S., TÜRKŞEN Ö., Erginel N.

JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING, cilt.36, sa.6, ss.527-542, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36 Sayı: 6
  • Basım Tarihi: 2021
  • Dergi Adı: JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, zbMATH
  • Sayfa Sayıları: ss.527-542
  • Anahtar Kelimeler: Intuitionistic fuzzy hypothesis, intuitionistic fuzzy number, bootstrap method, population mean, NEYMAN-PEARSON-LEMMA, STATISTICAL HYPOTHESES, BAYESIAN-APPROACH
  • Ankara Üniversitesi Adresli: Evet

Özet

Under vague and imprecise environment, data analysis methods are usually integrated with the fuzzy set theory. Intuitionistic methods sets are the extension of ordinary fuzzy sets whose aim is to incorporate the hesitancy of experts into their model. In this paper, novel intuitionistic fuzzy parametric approaches to statistical hypotheses testing for the population mean based on intuitionistic fuzzy data and intuitionistic fuzzy hypotheses are presented. First, bootstrap method is applied and then intuitionistic fuzzy test statistics is obtained. Applications of one sided and two sided hypotheses are provided.