Estimation for the Rayleigh distribution based on Type I hybrid censored sample

Kwon, Byongwon; Lee, Kyeong‐Jun; Cho, Youngseuk

doi:10.7465/jkdi.2014.25.2.431

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…These Eq.s are in implicit form, so it may be subsequently solved with a numerical method such as Newton-Raphson method. See for example the work of Cho et al (2013), Kwon et al (2014), and Shin et al (2014). The MLE of entropy function may be obtained by replacing (λ 1 , λ 2 ) by (λ 1 ,λ 2 ) in Eq.…”

Section: Maximum Likelihood Estimationmentioning

confidence: 99%

Bayes estimation of entropy of exponential distribution based on multiply Type II censored competing risks data

Lee¹,

Cho

2015

Journal of the Korean Data and Information Science Society

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In lifetime data analysis, it is generally known that the lifetimes of test items may not be recorded exactly. There are also situations wherein the withdrawal of items prior to failure is prearranged in order to decrease the time or cost associated with experience. Moreover, it is generally known that more than one cause or risk factor may be present at the same time. Therefore, analysis of censored competing risks data are needed. In this article, we derive the Bayes estimators for the entropy function under the exponential distribution with an unknown scale parameter based on multiply Type II censored competing risks data. The Bayes estimators of entropy function for the exponential distribution with multiply Type II censored competing risks data under the squared error loss function (SELF), precautionary loss function (PLF) and DeGroot loss function (DLF) are provided. Lindley's approximate method is used to compute these estimators. We compare the proposed Bayes estimators in the sense of the mean squared error (MSE) for various multiply Type II censored competing risks data. Finally, a real data set has been analyzed for illustrative purposes.

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Section: Maximum Likelihood Estimationmentioning

confidence: 99%

Bayes estimation of entropy of exponential distribution based on multiply Type II censored competing risks data

Lee¹,

Cho

2015

Journal of the Korean Data and Information Science Society

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“…See for example the work of Lee et al (2014), Kwon et al (2014), Lee et al (2013), and Lee et al (2012).…”

Section: Approximate Maximum Likelihood Estimatorsmentioning

confidence: 99%

Estimation of the half-logistic distribution based on multiply Type I hybrid censored sample

Shin¹,

Kim²,

Lee³

2014

Journal of the Korean Data and Information Science Society

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In this paper, we consider maximum likelihood estimators of the location and scale parameters for the half-logistic distribution when samples are multiply Type I hybrid censored. The scale parameter is estimated by approximate maximum likelihood estimation methods using two different Taylor series expansion types (σI,σII). We compare the estimators in the sense of the root mean square error (RMSE). The simulation procedure is repeated 10,000 times for the sample size n=20 and 40 and various censored schemes. The approximate MLE of the second type is better than that of the first type in the sense of the RMSE. Further an illustrative example with the real data is presented.

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Analysis of a new jointly hybrid censored Rayleigh populations

Elshahhat,

Ahmad,

Rabaiah

et al. 2024

MATH

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<abstract><p>When a researcher wants to perform a life-test comparison study of items made by two separate lines inside the same institution, joint censoring strategies are particularly important. In this paper, we present a new joint Type-Ⅰ hybrid censoring that enables an experimenter to stop the investigation as soon as a pre-specified number of failures or time is first achieved. In the context of newly censored data, the estimates of the unknown mean lifetimes of two different Rayleigh populations are acquired using maximum likelihood and Bayesian inferential techniques. The normality characteristic of classical estimators is used to offer asymptotic confidence interval bounds for each unknown parameter. Against gamma conjugate priors, the Bayes estimators and related credible intervals are gathered about symmetric and asymmetric loss functions. Since classical and Bayes estimators are acquired in closed form, simulation tests can be easily made to evaluate the effectiveness of the proposed methodologies. The efficiency of the suggested approaches is examined in terms of four metrics, namely: Root mean squared error, average relative absolute bias, average confidence length, and coverage probability. To demonstrate the applicability of the offered approaches to real events, two real applications employing data sets from the engineering area are analyzed. As a result, when the experimenter's primary goal is to complete the test as soon as the total number of failures or the threshold period is recorded, the numerical results reveal that the recommended strategy is adaptable and very helpful in completing the study.</p></abstract>

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Estimation for the Rayleigh distribution based on Type I hybrid censored sample

Cited by 3 publications

References 13 publications

Bayes estimation of entropy of exponential distribution based on multiply Type II censored competing risks data

Bayes estimation of entropy of exponential distribution based on multiply Type II censored competing risks data

Estimation of the half-logistic distribution based on multiply Type I hybrid censored sample

Analysis of a new jointly hybrid censored Rayleigh populations

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