Statistical Analysis Based on Adaptive Progressive Hybrid Censored Sample From Alpha Power Generalized Exponential Distribution

Yan, Zaizai; Wang, Na

doi:10.1109/access.2020.2981497

Cited by 6 publications

(4 citation statements)

References 18 publications

(17 reference statements)

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“…e posterior likelihood can be represented to be proportional to the product of the likelihood given in equation (13) and the joint prior's densities given by equation (22). at is,…”

Section: Bayesian Estimationmentioning

confidence: 99%

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The Weibull Generalized Exponential Distribution with Censored Sample: Estimation and Application on Real Data

et al. 2021

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This paper is concerned with the estimation of the Weibull generalized exponential distribution (WGED) parameters based on the adaptive Type-II progressive (ATIIP) censored sample. Maximum likelihood estimation (MLE), maximum product spacing (MPS), and Bayesian estimation based on Markov chain Monte Carlo (MCMC) methods have been determined to find the best estimation method. The Monte Carlo simulation is used to compare the three methods of estimation based on the ATIIP-censored sample, and also, we made a bootstrap confidence interval estimation. We will analyze data related to the distribution about single carbon fiber and electrical data as real data cases to show how the schemes work in practice.

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“…e posterior likelihood can be represented to be proportional to the product of the likelihood given in equation (13) and the joint prior's densities given by equation (22). at is,…”

Section: Bayesian Estimationmentioning

confidence: 99%

“…Otherwise, once the experiment time passes time T, but the number of observed failures has not reached m, we will terminate the experiment. Many authors had discussed applications under ATIIPCS using different lifetime distributions, for example, see [17][18][19][20][21] and [22].…”

Section: Introductionmentioning

confidence: 99%

The Weibull Generalized Exponential Distribution with Censored Sample: Estimation and Application on Real Data

et al. 2021

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“…Conventional Type I and II censoring schemes cannot be used if the experimenter wants to remove the live experimental unit at a point other than the final end point of the experiment. Therefore, recently, Pr2CS and Ad1PHCS have become quite popular in a life-testing problem and reliability analysis [7][8][9][10][11]. Although Pr2CS and Ad1PHCS assure a pre-assigned number of failures, they have the drawback that it might take a long time to observe a pre-assigned number of failures and terminate the test.…”

Section: Introductionmentioning

confidence: 99%

Exact Inference for an Exponential Parameter under Generalized Adaptive Progressive Hybrid Censored Competing Risks Data

Cho

Lee

2020

Symmetry

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It is known that the lifetimes of items may not be recorded exactly. In addition, it is known that more than one risk factor (RisF) may be present at the same time. In this paper, we discuss exact likelihood inference for competing risk model (CoRiM) with generalized adaptive progressive hybrid censored exponential data. We derive the conditional moment generating function (ConMGF) of the maximum likelihood estimators of scale parameters of exponential distribution (ExpD) and the resulting lower confidence bound under generalized adaptive progressive hybrid censoring scheme (GeAdPHCS). From the example data, it can be seen that the PDF of MLE is almost symmetrical.

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“…Moreover, the simulation study illustrates that the normal approximation is satisfactory for moderate and large sample sizes. Finally, with the established asymptotic theory, we can further benefit interval estimates [30], hypothesis tests [31]and stochastic control design [32]in a theoretical basis.…”

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confidence: 99%

Consistency and Asymptotic Normality of the Maximum Likelihood Estimator in GaGLM

Wang

Qin

2022

IEEE Access

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The Gamma distribution based generalized linear model (GaGLM) is a kind of statistical model feasible for the positive value of a non-stationary stochastic system, in which the location and the scale are regressed by the corresponding explanatory variables. This paper theoretically investigates the asymptotic properties of maximum likelihood estimates (MLE) of GaGLM, which can benefit the further interval estimates, hypothesis tests and stochastic control design. First, the score function and the Fisher information matrix for GaGLM are derived. Then, the Lyapunov condition is derived to ensure the asymptotic normality of the score function normalized by the Fisher information matrix. Based on this condition, the asymptotic normality of the MLE of GaGLM is proven. Finally, a numerical example is given to testify the asymptotic properties obtained in the research. The numerical results indicate that the MLE of GaGLM converged to a normal distribution as the number of sample measurements increased.INDEX TERMS Gamma distribution, Gamma regression, consistency and asymptotic normality, central limit theorem, maximum likelihood estimator.

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Statistical Analysis Based on Adaptive Progressive Hybrid Censored Sample From Alpha Power Generalized Exponential Distribution

Cited by 6 publications

References 18 publications

The Weibull Generalized Exponential Distribution with Censored Sample: Estimation and Application on Real Data

The Weibull Generalized Exponential Distribution with Censored Sample: Estimation and Application on Real Data

Exact Inference for an Exponential Parameter under Generalized Adaptive Progressive Hybrid Censored Competing Risks Data

Consistency and Asymptotic Normality of the Maximum Likelihood Estimator in GaGLM

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