Classical and Bayesian Inference of Conditional Stress-Strength Model under Kumaraswamy Distribution. (31st July 2021)

• Record Type: Journal Article
• Authors: Riad, Fathy H.; Saber, Mohammad Mehdi; Taghipour, Mehrdad; El-Raouf, M. M. Abd
• Other Names: Khalil Ahmed Mostafa Academic Editor.
• Is Part Of: Computational intelligence and neuroscience. Volume 2021(2021)
• Publication Date: 2021-07-31
• Subjects: Neurosciences -- Data processing -- Periodicals; Computational intelligence -- Periodicals; Computational neuroscience -- Periodicals; 612.80285
• DOI: 10.1155/2021/1087871
• Languages: English
• ISSNs: 1687-5265

Abstract

Abstract : Stress-strength models have been frequently studied in recent years. An applicable extension of these models is conditional stress-strength models. The maximum likelihood estimator of conditional stress-strength models, asymptotic distribution of this estimator, and its confidence intervals are obtained for Kumaraswamy distribution. In addition, Bayesian estimation and bootstrap method are applied to the model.