Estimation and prediction of Marshall–Olkin extended exponential distribution under progressively type-II censored data

Dey, Sanku; Nassar, Mazen; Maurya, Raj Kamal; Tripathi, Yogesh Mani

doi:10.1080/00949655.2018.1458310

Cited by 17 publications

(14 citation statements)

References 21 publications

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“…5 indicate that the MKR distribution is suitable for modeling the given DS. To estimate the parameters of the MKR distribution based on PT-IIC scheme we consider to use the same PT-IIC samples used by [20] and generated from the original DS displayed in Table 4. Dey et al [20] generated three PT-IIC samples with different schemes as presented in Table 6.…”

Section: Discussionmentioning

confidence: 99%

“…To estimate the parameters of the MKR distribution based on PT-IIC scheme we consider to use the same PT-IIC samples used by [20] and generated from the original DS displayed in Table 4. Dey et al [20] generated three PT-IIC samples with different schemes as presented in Table 6. Using the generated PT-IIC samples in Table 6, the MLEs and MPSEs are obtained and displayed in Table 7.…”

Section: Discussionmentioning

confidence: 99%

“…− R r−1 units are removed and the experiment terminates. Over the decade, there have been several studies to parameter estimation based on PT-IIC scheme, see for example [18][19][20][21]. See also for more details [22,23].…”

Section: Parameter Estimation Under Pt-iic Samplementioning

confidence: 99%

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A New Rayleigh Distribution: Properties and Estimation Based on Progressive Type-II Censored Data with an Application

Algarni¹,

Almarashi²

2022

Computer Modeling in Engineering &Amp; Sciences

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In this paper, we propose a new extension of the traditional Rayleigh distribution called the modified Kies Rayleigh distribution. The new distribution contains one scale and one shape parameter and its hazard rate function can be increasing and bathtub-shaped. Some mathematical properties of the new distribution are derived including quantiles and moments. The parameters of modified Kies Rayleigh distribution are estimated based on progressively Type-II censored data. For this purpose, we consider two estimation methods, namely maximum likelihood and maximum product of spacing estimation methods. To compare the efficiency of the proposed estimators, a simulation study is carried out. To show the applicability of the new model as well as the estimation methods, one real data for failure times of software is analyzed. Based on the empirical parts, we can conclude that the proposed model can be considered as a good model in the field of life testing and reliability analysis compared with other competing models.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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A New Rayleigh Distribution: Properties and Estimation Based on Progressive Type-II Censored Data with an Application

Algarni¹,

Almarashi²

2022

Computer Modeling in Engineering &Amp; Sciences

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“…In the existing literature, various prior distributions have been proposed for the unknown parameters of a particular distribution of interest. For example, previous studies also considered independent gamma priors for the parameters of Weibull, Nadarajah Haghigi, Marshallolkin extended exponential, and exponentiated moment exponential distributions, respectively. However, Arnold and Press mentioned that there is clearly no way in which one can say that one prior is better than other.…”

Section: Estimation Of Gsk When μ Is Unknownmentioning

confidence: 99%

Reliability estimation of a multicomponent stress‐strength model for unit Gompertz distribution under progressive Type II censoring

Jha

Dey²,

Alotaibi

et al. 2020

Quality & Reliability Eng

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We consider the problem of estimating multicomponent stress‐strength (MSS) reliability under progressive Type II censoring when stress and strength variables follow unit Gompertz distributions with common scale parameter. We estimate MSS reliability under frequentist and Bayesian approaches. Bayes estimates are obtained by using Lindley approximation and Metropolis‐Hastings algorithm methods. Further, we obtain uniformly minimum variance unbiased estimates of the reliability when common scale parameter is known. Asymptotic, bootstrap confidence interval and highest posterior density credible intervals have been constructed. We perform Monte Carlo simulations to compare the performance of proposed estimates and also present a discussion. Finally, three real data sets are analyzed for illustrative purposes.

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“…For some more references in recent years where the problem prediction of censored or future observation based on Bayesian framework under progressive type-II censoring, we refer to Kayal et al (2017), Singh et al (2017), Dey et al (2018) and Bdair et al (2019). To the best of our knowledge, nobody has considered estimation and prediction for a generalized Fre ´chet distribution with CDF given in (1.1) based on the progressive type-II censored sample.…”

Section: Introductionmentioning

confidence: 99%

Estimation for the generalized Fréchet distribution under progressive censoring scheme

Maiti

Kayal

2019

Int J Syst Assur Eng Manag

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This paper takes into account the estimation of the unknown model parameters and the reliability characteristics for a generalized Fre ´chet distribution under progressive type-II censored sample. Maximum likelihood estimates are obtained. We calculate asymptotic confidence intervals and also compare in terms of their coverage probabilities for the unknown parameters, and the reliability and hazard rate functions. Further, Bayes estimates are derived with respect to various balanced type symmetric as well as asymmetric loss functions. Note that it is impossible to get the estimates in closed-form. So, we adopt importance sampling method in computing the Bayes estimates. Furthermore, we consider one-sample and twosample prediction problems under Bayesian framework. In this case, the appropriate predictive intervals are proposed. Monte Carlo simulations are performed to observe the performance of various estimates. Moreover, results from simulation studies indicating the performance of the proposed methods are included. Finally, a real dataset is considered and analyzed for the illustration of the inferential procedures studied in this paper.

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Estimation and prediction of Marshall–Olkin extended exponential distribution under progressively type-II censored data

Cited by 17 publications

References 21 publications

A New Rayleigh Distribution: Properties and Estimation Based on Progressive Type-II Censored Data with an Application

A New Rayleigh Distribution: Properties and Estimation Based on Progressive Type-II Censored Data with an Application

Reliability estimation of a multicomponent stress‐strength model for unit Gompertz distribution under progressive Type II censoring

Estimation for the generalized Fréchet distribution under progressive censoring scheme

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