Testing exponentiality for imprecise data and its application

被引：4
作者：
Zendehdel, J. [1 ]
Rezaei, M. [1 ]
Akbari, M. G. [1 ]
Zarei, R. [2 ]
Noughabi, H. Alizadeh [1 ]
机构：
[1] Univ Birjand, Fac Math & Stat, Dept Stat, Birjand, Iran
[2] Univ Guilan, Fac Math Sci, Dept Stat, Guilan, Iran
来源：
SOFT COMPUTING | 2018年 / 22卷 / 10期
关键词：
Goodness-of-fit test; Exponential distribution; Fuzzy data set; alpha-Pessimistic; Monte Carlo simulation; MARKOVIAN JUMP SYSTEMS; FUZZY RANDOM-VARIABLES; OF-FIT TESTS; STATISTICAL HYPOTHESES;
D O I：
10.1007/s00500-017-2566-y
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The goodness-of-fit test for a given data set is an important problem in statistical inference and its applications. In this paper, we consider this problem for the exponential distribution which is widely used in the various areas under fuzzy environment. To this end, we need an approach that the most commonly used tests in statistics such as Kolmogorov-Smirnov and Anderson-Darling are made usable for fuzzy data set. For this purpose, we use the alpha-pessimistic technique and Monte Carlo simulation method.
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页码：3301 / 3312
页数：12
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