Improving Lifetime Data Modeling via a Comparative Examination of the Modified Weibull Distribution

• Shahid Mohammad

  English

  Author

In this research, a novel two-parameter univariate distribution is presented for a non-negative domain,
which is an adaptation of the Weibull distribution. Azzalini and Capitanio's framework is the source of this
distribution, which shows a hazard rate that increases monotonically. Key statistical features, such as reliability
functions, moments, moment-generating functions, and order statistics, may be expressed in closed form. A
formula is developed for the purpose of generating random numbers. Parameter inference makes use of the greatest
likelihood. The dependability of these estimators under different scenarios is shown in a simulation exercise. Two
real-world datasets, waiting times and carbon fiber tensile strength, are used to evaluate the model's practical
usefulness. Validity tool tests and quantile-quantile plots demonstrate that the suggested model is more adaptable
and accurate in fitting real-world issues than the alternatives that were chosen.

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