Z-fuzzy hypothesis testing in statistical decision making

被引：11

作者：

Haktanir, Elif ^{[1
,2
]}

Kahraman, Cengiz ^{[1
]}

机构：

[1] Istanbul Tech Univ, Dept Ind Engn, TR-34367 Istanbul, Turkey

[2] Altinbas Univ, Dept Ind Engn, Istanbul, Turkey

来源：

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2019年 / 37卷 / 05期

关键词：

Z-fuzzy number; hypothesis testing; statistical decision making; restriction function; reliability function; NEYMAN-PEARSON-LEMMA; BAYESIAN-APPROACH;

D O I：

10.3233/JIFS-182700

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Hypothesis tests are a statistical decision-making tool for testing if a hypothesized parameter value is supported by the sample data or not. Vagueness and impreciseness in the sample data require fuzzy techniques to be employed in the analysis. These techniques can be based on intuitionistic fuzzy sets, hesitant fuzzy sets, type-2 fuzzy sets, neutrosophic sets, or spherical fuzzy sets. In this paper, Z-fuzzy numbers are used to capture the vagueness in the sample data and develop Z-fuzzy hypothesis testing. A Z-fuzzy number is represented by a restriction function that is usually a triangular or trapezoidal fuzzy number and a reliability function representing the confidence level to the restriction function. Illustrative examples for left and right sided hypothesis testing and sensitivity analyses are presented.

引用

页码：6545 / 6555

页数：11

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