On progressively censored inverted exponentiated Rayleigh distribution

Maurya, Raj Kamal; Tripathi, Yogesh Mani; Sen, Tanmay; Rastogi, Manoj Kumar

doi:10.1080/00949655.2018.1558225

Cited by 18 publications

(7 citation statements)

References 27 publications

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“…For a comprehensive review of the censoring technique mentioned above, details can be found in the monographs by Balakrishnan and Aggarwala (2000) and Balakrishnan and Cramer (2014). Among others, one may refer to Ng et al (2002), Tse and Yang (2003), Wu et al (2005), Burkschat et al (2006), Pradhan and Kundu (2009), Rastogi and Tripathi (2012), Singh et al (2015), Bhattacharya et al (2016), Kayal et al (2017), Wang (2018), Maurya et al (2019), Mahto and Tripathi (2020), Lodhi et al (2021), Bhattacharya and Balakrishnan (2022) and Singh et al (2023), investigated Type-II censoring for the Inverted Exponentiated Pareto distributions using maximum likelihood and Pivotal methods. Recently, Kumari et al (2023) and the references cited therein.…”

Section: Introductionmentioning

confidence: 99%

Reliability Inference for Gompertz Distribution Using Pivotal Method under Block Progressive Type-II Censored Data

Kumari,

Tripathi,

Gangopadhyay

et al. 2024

Preprint

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In this paper, we primarily focus on making important deductions regarding the estimates of survival characteristics in the context of block progressive censored data. Specifically, we examine the reliability function, hazard rate function, median time to failure, and variations among different test facilities. Our analysis is centered on the lifetime of test units following the Gompertz distribution. We derive maximum likelihood estimators for unknown quantities and investigate their properties regarding existence and uniqueness. Additionally, we construct approximate confidence intervals for all survival characteristics using the delta method and likelihood theory. Moreover, we develop point and generalized confidence interval estimators through a pivotal quantity-based method. To evaluate the performance of our proposed approaches, we conduct a simulation study and find that the pivotal quantity-based approach yields superior estimation results. Finally, we apply the proposed estimates to analyze real-world data, demonstrating their effectiveness.

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Section: Introductionmentioning

confidence: 99%

Reliability Inference for Gompertz Distribution Using Pivotal Method under Block Progressive Type-II Censored Data

Kumari,

Tripathi,

Gangopadhyay

et al. 2024

Preprint

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“…Various properties of this method are discussed in depth in treatise of Balakrishnan and Aggarwala 25 and Balakrishnan and Cramer. 26 See also Wu et al, 27 Rastogi and Tripathi 28 Maurya et al, 29 Maurya et al, 30 Mahto et al, 31 Chandra et al, 32 Hua and Gui 33 for important literature on this method of inference.…”

Section: Introductionmentioning

confidence: 99%

Estimation in a multicomponent stress-strength model for progressive censored lognormal distribution

Singh

Mahto

Tripathi

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part O:

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We consider estimation of multicomponent stress-strength reliability under classical as well as Bayesian approaches when stress-strength components follow lognormal distributions and data are observed under progressive censoring. Various estimates are obtained by sequentially considering one parameter common and unknown. Different expressions for the reliability are evaluated under these cases. For both the cases, we obtain different estimates of considered parametric function using likelihood, Lindley and repeated sampling methods. Asymptotic and credible intervals are also obtained. Extensive simulations are conducted to examine the behavior of all estimates under various censoring schemes. We finally present analysis of a real life example from application purposes.

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“…By considering Q (1/ x ) = 1/ x , 1/ x 2 and log)(1+1/x, we find inverted exponentiated exponential, inverted exponentiated Rayleigh and inverted exponentiated Pareto distributions to be special cases of IED ( α , λ ) family. One may further refer to Maurya et al. (2019), Gao et al.…”

Section: Introductionmentioning

confidence: 99%

“…By considering Q(1/x) 5 1/x, 1/x 2 and log 1 þ 1= ð xÞ, we find inverted exponentiated exponential, inverted exponentiated Rayleigh and inverted exponentiated Pareto distributions to be special cases of IED(α, λ) family. One may further refer to Maurya et al (2019), Gao et al (2020), Wang et al (2020) for some further discussion on the applicability of this family of densities in real-life situations.…”

Section: Introductionmentioning

confidence: 99%

Estimation of stress–strength reliability for inverse exponentiated distributions with application

Kumari

Lodhi²,

Tripathi³

et al. 2022

IJQRM

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PurposeInferences for multicomponent reliability is derived for a family of inverted exponentiated densities having common scale and different shape parameters.Design/methodology/approachDifferent estimates for multicomponent reliability is derived from frequentist viewpoint. Two bootstrap confidence intervals of this parametric function are also constructed.FindingsForm a Monte-Carlo simulation study, the authors find that estimates obtained from maximum product spacing and Right-tail Anderson–Darling procedures provide better point and interval estimates of the reliability. Also the maximum likelihood estimate competes good with these estimates.Originality/valueIn literature several distributions are introduced and studied in lifetime analysis. Among others, exponentiated distributions have found wide applications in such studies. In this regard the authors obtain various frequentist estimates for the multicomponent reliability by considering inverted exponentiated distributions.

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On progressively censored inverted exponentiated Rayleigh distribution

Cited by 18 publications

References 27 publications

Reliability Inference for Gompertz Distribution Using Pivotal Method under Block Progressive Type-II Censored Data

Reliability Inference for Gompertz Distribution Using Pivotal Method under Block Progressive Type-II Censored Data

Estimation in a multicomponent stress-strength model for progressive censored lognormal distribution

Estimation of stress–strength reliability for inverse exponentiated distributions with application

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