出版日期：2025-06-14 00:00:00

著者：Shuo-Jye Wu; Yao-Ting Tseng ; Coskun Kus

著錄名稱、卷期、頁數：The Journal of Supercomputing 81，1029

摘要：In this paper, we investigate parameter inference for the Kumaraswamy distribution based on progressively type-II censored data. Our approach involves employing the method of maximum likelihood to derive point estimates for the model parameters. We establish the existence and uniqueness of these maximum likelihood estimators. Additionally, we present pivotal quantities that enable the construction of exact confidence intervals and joint confidence regions for the model parameters. To assess the performance of our proposed estimation techniques, we conduct comprehensive simulation studies. In conclusion, we apply the introduced estimation methods to analyze and discuss the results obtained from three real datasets, providing practical insights into their performance. These exact joint confidence regions can be directly utilized to construct confidence bounds for various reliability indices and quality control measures, enhancing their applicability in industrial settings.

關鍵字：Confidence interval ;Confidence region ;Kumaraswamy distribution; Maximum likelihood estimation ;Pivotal quantity ;Progressive type-II censoring

語言：en_US

期刊性質：國外

收錄於：SCI Scopus

審稿制度：是

國別：USA

出版型式：電子版,紙本