Assist. Prof. Dr. Thamer Manshi research activity focuses on advanced statistical theory and applied modeling, with emphasis on reliability distributions, dependent competing risks data, and complex censoring schemes. The work advances statistical inference under progressively hybrid censoring and bivariate dependence to improve model flexibility and estimation accuracy. Key contributions include the development of new bivariate distributions with applications in reliability engineering, biomedical analysis, and risk assessment. Methodological approaches integrate likelihood-based inference, distributional theory, and simulation studies supported by R and SPSS. Research outputs include 2 peer-reviewed documents published in international journals. These works have received 2 citations from 2 documents, reflecting emerging scholarly impact. The current h-index is 1 (h-index view disabled in preview mode).
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