Contributions to the lifetime distributions
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The research presented in this thesis, Contributions to the Lifetime Distributions introduces
newlineinnovative statistical models and estimation techniques for analyzing lifetime data.
newlineThe thesis significantly advances the field by developing new distributions and exploring
newlinetheir practical applications.
newlineOne primary contribution is the Arvind distribution, a new continuous lifetime model
newlinedemonstrating flexibility through diverse density and hazard rate functions. This model
newlineeffectively handles data related to climate, COVID-19, and reliability, showcasing its
newlinepractical relevance. Additionally, the DBHE distribution is proposed for managing overdispersed,
newlinepositively skewed, and decreasing failure rate data, proving useful for complete
newlineand censored datasets. Another notable development is the ExDLi distribution, which
newlineprovides a versatile approach for analyzing count data with various dispersion and skewness
newlinecharacteristics.
newlineThe thesis extends stress-strength reliability models to complex systems with multiple
newlinestress and strength variables. For the NML distribution under progressive Type-II censoring,
newlinethe effectiveness of these models for real-world reliability assessments is highlighted.
newlineIt also explores the MRS function, enhancing our understanding of system remaining
newlinestrength. Implementing these models in real-time monitoring systems for climate analysis,
newlinepandemic tracking, and mechanical systems is proposed to enhance their practical
newlineutility. Additionally, methods for estimating the S-S reliability parameter in scenarios
newlinewhere the system s strength is bounded by two stresses (lower and upper), particularly
newlinefor Rayleigh distributions under PFF censoring, are presented. The superior performance
newline145
newlineChapter 7. Conclusions and Future Perspectives 146
newlineof Bayesian estimators with informative priors, especially for smaller values of and#951;, is emphasized.
newlineThe thesis suggests applying new stress-strength setups to fields like medical
newlineresearch, finance, and environmental studies to address complex real-world data scenarios.