Pivot-Based Parameter Estimation for the Gumbel Distribution with Progressive Type-II Censoring Scheme

บทคัดย่อ

In this article, we propose a parameter estimation method based on pivotal quantities for the Gumbel distribution following the progressive Type-II censoring scheme. We also conduct a simulation study to assess the efficiency of the proposed method compared to the classical maximum likelihood estimation method. Simulation results indicate that pivot-based method outperforms the likelihood method in terms of both bias and mean squared error, particularly for the case of small sample sizes. Finally, we apply the proposed method to two real applications and evaluate its performance through different goodness-of-fit criteria. The results demonstrate strong performance of the method across both applications.