Bayes estimation based on -record data from a general class of distributions under balanced type loss functions

Ahmadi, Jafar; Jozani, Mohammad Jafari; Marchand, Éric; Parsian, Ahmad

doi:10.1016/j.jspi.2008.07.008

Cited by 64 publications

(36 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A general development with regard to Bayes estimators under L ρ,w,δ 0 is given, namely by relating such estimators to Bayes solutions to the unbalanced case, i.e., L ρ,w,δ 0 with w = 0. L ρ,w,δ 0 can be specialized to various choices of loss function, such as for SEL, LL and EL functions (Ahmadi et al [18]). By choosing ρ(θ, δ) = (δ − θ) 2 , Equation (13) reduced to the balanced squared error loss (BSEL) function, in the form:…”

Section: Bayes Estimation Based On Balanced Loss Functionmentioning

confidence: 99%

Estimating the Entropy of a Weibull Distribution under Generalized Progressive Hybrid Censoring

Cho

Sun

Lee

2015

Entropy

View full text Add to dashboard Cite

Recently, progressive hybrid censoring schemes have become quite popular in a life-testing problem and reliability analysis. However, the limitation of the progressive hybrid censoring scheme is that it cannot be applied when few failures occur before time T . Therefore, a generalized progressive hybrid censoring scheme was introduced. In this paper, the estimation of the entropy of a two-parameter Weibull distribution based on the generalized progressively censored sample has been considered. The Bayes estimators for the entropy of the Weibull distribution based on the symmetric and asymmetric loss functions, such as the squared error, linex and general entropy loss functions, are provided. The Bayes estimators cannot be obtained explicitly, and Lindley's approximation is used to obtain the Bayes estimators. Simulation experiments are performed to see the effectiveness of the different estimators. Finally, a real dataset has been analyzed for illustrative purposes.

show abstract

Section: Bayes Estimation Based On Balanced Loss Functionmentioning

confidence: 99%

Estimating the Entropy of a Weibull Distribution under Generalized Progressive Hybrid Censoring

Cho

Sun

Lee

2015

Entropy

View full text Add to dashboard Cite

show abstract

“…Based on balanced SE loss function, the Bayes estimator of the function of parameters U = U(Θ), Θ = (γ, σ 1 , σ 2 ) is given by Ahmadi et al (2009) …”

Section: Bayes Estimationmentioning

confidence: 99%

Parametric inference on step-stress accelerated life testing for the extension of exponential distribution under progressive type-II censoring

El-Din

Abu-Youssef

Ali

et al. 2016

CSAM

View full text Add to dashboard Cite

In this paper, a simple step-stress accelerated life test (ALT) under progressive type-II censoring is considered. Progressive type-II censoring and accelerated life testing are provided to decrease the lifetime of testing and lower test expenses. The cumulative exposure model is assumed when the lifetime of test units follows an extension of the exponential distribution. Maximum likelihood estimates (MLEs) and Bayes estimates (BEs) of the model parameters are also obtained. In addition, a real dataset is analyzed to illustrate the proposed procedures. Approximate, bootstrap and credible confidence intervals (CIs) of the estimators are then derived. Finally, the accuracy of the MLEs and BEs for the model parameters is investigated through simulation studies.

show abstract

“…We shall use the following form BLF introduced by Ahmadi et al [15] L q ρ,ω,δ 0 (Λ(α), δ) = ωq(α)ρ(δ 0 , δ)…”

Section: Introductionmentioning

confidence: 99%

E-Bayesian estimation for the geometric model based on record statistics

Okasha

Wang

2016

Applied Mathematical Modelling

View full text Add to dashboard Cite

This paper focuses on using the new method (E-Bayesian) for computing estimates for the parameter and reliability function of the geometric distribution. The estimates are derived based on a conjugate prior for the scale parameter. Our computations are based on the balanced loss function which contains the symmetric and asymmetric loss functions as special cases. The results have been specialized to upper record values. Examples using both real and simulated record values are used to illustrate the application of the results. The results may be of interest in a situation where only record values are stored.

show abstract

Bayes estimation based on -record data from a general class of distributions under balanced type loss functions

Cited by 64 publications

References 14 publications

Estimating the Entropy of a Weibull Distribution under Generalized Progressive Hybrid Censoring

Estimating the Entropy of a Weibull Distribution under Generalized Progressive Hybrid Censoring

Parametric inference on step-stress accelerated life testing for the extension of exponential distribution under progressive type-II censoring

E-Bayesian estimation for the geometric model based on record statistics

Contact Info

Product

Resources

About