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<p>We propose a novel entropy-based goodness-of-fit test for the Weibull distribution tailored to fuzzy lifetime data. By transforming fuzzy Weibull observations into exponential form, the method exploits the maximum entropy property of the exponential distribution and computes an integrated entropy-based statistic across fuzzy membership levels, effectively capturing data imprecision. The test’s critical values and statistical power are evaluated via extensive Monte Carlo simulations, demonstrating its reliability. Application to real-world fuzzy lifetime data illustrates the method’s practical effectiveness in reliability and risk assessment under uncertainty, highlighting its robustness and applicability.</p>

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Entropy-based goodness-of-fit test for the Weibull distribution under fuzzy data

  • 期刊论文

  • 发表日期：

    2026年5月12日

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  • Hadi Alizadeh Noughabi

摘要

We propose a novel entropy-based goodness-of-fit test for the Weibull distribution tailored to fuzzy lifetime data. By transforming fuzzy Weibull observations into exponential form, the method exploits the maximum entropy property of the exponential distribution and computes an integrated entropy-based statistic across fuzzy membership levels, effectively capturing data imprecision. The test’s critical values and statistical power are evaluated via extensive Monte Carlo simulations, demonstrating its reliability. Application to real-world fuzzy lifetime data illustrates the method’s practical effectiveness in reliability and risk assessment under uncertainty, highlighting its robustness and applicability.