期刊
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
卷 421, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.cam.2022.114836
关键词
Matusita measure; Progressive first-failure censored data; Generalized inverted exponential distribution; Maximum likelihood estimation; Generalized estimation; Likelihood ratio test
This paper investigates the inference for the Matusita measure between independent Generalized Inverted Exponential Distributions (GIEDs) under progressive first-failure censoring. The maximum likelihood estimator for the Matusita measure is established when the GIEDs have a common scale but different shape parameters, along with the existence and uniqueness of model estimators. An approximate confidence interval and alternative point and interval estimates based on proposed pivotal quantities are constructed. Bootstrap confidence intervals are also provided for comparison. Additionally, likelihood and generalized estimates for the Matusita measure are discussed when the two GIEDs have unequal parameters. Likelihood ratio testing is provided for comparing the equivalence of the interested parameters. Extensive simulation studies are conducted to evaluate the performances of different methods, and two real-life examples are presented for application.
Inference for Matusita measure between independent generalized inverted exponential distributions (GIEDs) is investigated under progressive first-failure censoring. When both GIEDs have common scale but different shape parameters, maximum likelihood estimator of the Matusita measure along with the existence and uniqueness of model estimators are established. Approximate confidence interval is constructed in conse-quence. Alternative generalized point and interval estimates are further constructed based on proposed pivotal quantities. For comparison, bootstrap confidence intervals are also provided. In addition, likelihood and generalized estimates for the Matusita measure are also discussed when two GIEDs have unequal parameters. Further, likelihood ratio testing is provided for comparing the equivalence of the interested parameters. Finally, extensive simulation studies are carried out to evaluate the performances of different methods, and two real life examples are presented for application.(c) 2022 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据