Coefficient of Variation of Topp-Leone Distribution Under Adaptive Type-II Progressive Censoring Scheme: Bayesian and Non-Bayesian Approach

Abd-Elmougod, G. A.; El-Sayed, Mohamed A.; Abdel-Rahman, Essam O.

doi:10.1166/jctn.2015.4314

Cited by 14 publications

(6 citation statements)

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“…Different approximation techniques can be applied to overcome this problem, such as numerical integration, Lindley approximations, and the Markov chain Monte Carlo (MCMC) approach. This study adopts MCMC with an importance sample technique for computing Bayes estimators under the symmetric squared error loss function (SELF); see [37].…”

Section: Bayes Estimationmentioning

confidence: 99%

Burr XII Distribution for Disease Data Analysis in the Presence of a Partially Observed Failure Mode

et al. 2022

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Modeling competing failure modes is an important problem in engineering and survival analyses. Competing failure modes are partially observed in many applications and often pose a modeling challenge. This study discusses the inference for partially observed failure modes assuming a Burr XII distribution. In particular, we consider two failure modes, and the failure time data are collected under a hybrid type I censoring scheme. The model parameters are estimated using maximum likelihood and Bayesian methods under a symmetric squared error loss function, whereas the intervals estimation is done with three methods: asymptotic and credible confidence intervals. Besides a simulation study, a real-life data set is taken from individuals who live in an environment with several diseases to present the utility of the work. Additionally, a simulation study is constructed to measure and compare different estimation methods.

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Section: Bayes Estimationmentioning

confidence: 99%

Burr XII Distribution for Disease Data Analysis in the Presence of a Partially Observed Failure Mode

et al. 2022

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“…( 7) and hence, the maximum values of Log-likelihood eq. ( 8), Abd-Elmougod et al [13]. Therefore, we compute the first partial derivatives of eq.…”

Section: Point Maximum Likelihood Estimatorsmentioning

confidence: 99%

Statistical inference of type-I hybrid censored inverse Lomax samples

Almuhayfith

Al‐Bossly

2022

THERM SCI

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In this article, we adopted the classical and Bayesian approach to develop the problem of estimation and prediction of the inverse Lomax distribution under Type-I hybrid censored scheme. Firstly, we presented maximum likelihood estimators and Bayes estimators of the unknown parameters under consideration of squared error loss equation. In Bayesian approach, we used Markov chain Monte-Carlo method by applied importance sampling technique. Asymptotic confidence intervals and Bayes credible intervals are constructed. The estimators are tested by building sim?ulation study. Secondly, For given Type-I hybrid censoring sample Bayesian prediction of future order statistics are formulated (two-sample case). Finally, the numerical computations are adopted on a real data set for illustrating purpose.

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“…For applications of CV in, medical sciences, engineering, physics, chemistry and telecommunications see, Miller and Karson [9], Hamer et al [10], Reh and Sche er [11], Ahn [12] and Gong and Li [13]. Several authors studied CV in normal phenomena but the works in non normal phenomena are rare, see Soliman et al [14] and AbdElmougod et al [15]. The main aim of this paper iss to study CV of EED when the data obtained from type-II censoring experiment and the joint likelihood function as the form…”

Section: : the Population Mean µ Ofmentioning

confidence: 99%

Estimation for coefficient of variation of an extension of the exponential distribution under type-II censoring scheme

Bakoban

2017

Open Physics

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Abstract:The coefficient of variation [CV] has several applications in applied statistics. So in this paper, we adopt Bayesian and non-Bayesian approaches for the estimation of CV under type-II censored data from extension exponential distribution [EED]. The point and interval estimate of the CV are obtained for each of the maximum likelihood and parametric bootstrap techniques. Also the Bayesian approach with the help of MCMC method is presented. A real data set is presented and analyzed, hence the obtained results are used to assess the obtained theoretical results .

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Coefficient of Variation of Topp-Leone Distribution Under Adaptive Type-II Progressive Censoring Scheme: Bayesian and Non-Bayesian Approach

Cited by 14 publications

References 0 publications

Burr XII Distribution for Disease Data Analysis in the Presence of a Partially Observed Failure Mode

Burr XII Distribution for Disease Data Analysis in the Presence of a Partially Observed Failure Mode

Statistical inference of type-I hybrid censored inverse Lomax samples

Estimation for coefficient of variation of an extension of the exponential distribution under type-II censoring scheme

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