A simulation study of parameters for the censored shifted Gompertz mixture distribution: A Bayesian approach

Sindhu, Tabassum Naz; Aslam, Muhammad; Hussain, Zawar

doi:10.1080/09720510.2015.1103462

Cited by 15 publications

(7 citation statements)

References 13 publications

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“…For further discussion on distributions, see Ref. [21][22][23][24][25][26][27][28]. Figure 1 demonstrates the nonmonotonic behaviour of hazard rate function (hrf) of IWD.…”

Section: The Generalized Inverse Weibull Distributionmentioning

confidence: 99%

Reliability analysis incorporating exponentiated inverse Weibull distribution and inverse power law

Sindhu

Atangana

2021

Quality & Reliability Eng

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In reliability research, electronic devices are an important part of our lives and modelling their lives is the most difficult and fascinating area. To investigate the failure functioning of electronic equipments, reliability monitoring of systems is widely used. However, it is stated in the literature that one in five electronic system collapses are a consequence of degradation and saving energy and forecasting future losses, it is necessary to summarize the data through certain versatile models of probability . In current article, a model of reliability formed on inverse power law and generalized inverse Weibull model is suggested. This current distribution presents a clearer framework to modelling the efficiency and functionality lifespan of electronic equipments. In this article, an empirical analysis is discussed related to life cycle of a surface-mounted electrolytic capacitor (SMEC). In addition, it has noticed that evaluation of suggested distribution varies from classical model of inverse Weibull and that influences average time to failure (ATTF) of the studied capacitor. K E Y W O R D Selectronic devices, inverse power law, non-monotonic failure rate

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“…For further discussion on distributions, see Ref. [21][22][23][24][25][26][27][28]. Figure 1 demonstrates the nonmonotonic behaviour of hazard rate function (hrf) of IWD.…”

Section: The Generalized Inverse Weibull Distributionmentioning

confidence: 99%

Reliability analysis incorporating exponentiated inverse Weibull distribution and inverse power law

Sindhu

Atangana

2021

Quality & Reliability Eng

Self Cite

View full text Add to dashboard Cite

show abstract

“…The BE (Bayes estimator) of

is given under SELF

[21] , [22] , [23] , [24] , [25] , [26] as

in a similar fashion

and

. Additionally, Bayes risk is evaluated by

, where

…”

Section: Estimationmentioning

confidence: 99%

On the analysis of number of deaths due to Covid −19 outbreak data using a new class of distributions

2021

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“…[33] , [34] ) and also proposed a new two-component mixture model (see Sindhu et al. [35] , [36] , [37] , [38] , [39] , [40] , [41] ) of three-parameter MKNPF distribution.…”

Section: Introductionmentioning

confidence: 99%

A novel extended model with versatile shaped failure rate: Statistical inference with Covid -19 applications

2022

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A simulation study of parameters for the censored shifted Gompertz mixture distribution: A Bayesian approach

Cited by 15 publications

References 13 publications

Reliability analysis incorporating exponentiated inverse Weibull distribution and inverse power law

Reliability analysis incorporating exponentiated inverse Weibull distribution and inverse power law

On the analysis of number of deaths due to Covid −19 outbreak data using a new class of distributions

A novel extended model with versatile shaped failure rate: Statistical inference with Covid -19 applications

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