Parametric estimation plays a pivotal role in modeling reliability and survival data under complex censoring schemes. This study focuses on the estimation of parameters in flexible Weibull extension models when facing progressive Type-II censoring. The flexible Weibull extension is a versatile distribution capable of capturing a wide range of failure patterns. We propose an estimation method that harnesses the power of maximum likelihood estimation in conjunction with progressive Type-II censoring. Simulated and real-world data are employed to evaluate the method's performance, demonstrating its effectiveness in accurately estimating the parameters of the flexible Weibull extension model under this challenging censoring scenario.

Parametric Estimation, Flexible Weibull Extension, Progressive Type-II Censoring

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