• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.431-438
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• 2014

Type I hybrid censoring scheme is the combination of the Type I and Type II censoring scheme introduced by Epstein (1954). Epstein considered a hybrid censoring sampling scheme in which the life testing experiment is terminated at a random time $T^*$ which is the time that happens rst among the following two; time of the kth unit is observed or time of the experiment length set in advance. The likelihood function of this scheme from the Rayleigh distribution cannot be solved in a explicit solution and thus we approximate the function by the Taylor series expansion. In this process, we propose four dierent methods of expansion skill.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.47-64
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• 2020

In this paper, we derive some estimators of the scale parameter of the exponentiated half-logistic distribution based on the multiply Type-I hybrid censoring scheme. We assume that the shape parameter λ is known. We obtain the maximum likelihood estimator of the scale parameter σ. The scale parameter is estimated by approximating the given likelihood function using two different Taylor series expansions since the likelihood equation is not explicitly solved. We also obtain Bayes estimators using prior distribution. To obtain the Bayes estimators, we use the squared error loss function and general entropy loss function (shape parameter q = -0.5, 1.0). We also derive interval estimation such as the asymptotic confidence interval, the credible interval, and the highest posterior density interval. Finally, we compare the proposed estimators in the sense of the mean squared error through Monte Carlo simulation. The average length of 95% intervals and the corresponding coverage probability are also obtained.

• Communications for Statistical Applications and Methods
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• v.27 no.4
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• pp.469-486
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• 2020

Entropy is an important term in statistical mechanics that was originally defined in the second law of thermodynamics. In this paper, we consider the maximum likelihood estimation (MLE), maximum product spacings estimation (MPSE) and Bayesian estimation of the entropy of an inverse Weibull distribution (InW) under a generalized type I progressive hybrid censoring scheme (GePH). The MLE and MPSE of the entropy cannot be obtained in closed form; therefore, we propose using the Newton-Raphson algorithm to solve it. Further, the Bayesian estimators for the entropy of InW based on squared error loss function (SqL), precautionary loss function (PrL), general entropy loss function (GeL) and linex loss function (LiL) are derived. In addition, we derive the Lindley's approximate method (LiA) of the Bayesian estimates. Monte Carlo simulations are conducted to compare the results among MLE, MPSE, and Bayesian estimators. A real data set based on the GePH is also analyzed for illustrative purposes.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.1
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• pp.115-129
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• 1996

A reliability Acceptance Sampling Plan (RASP) is developed for testing the exponential mean lifetime under the periodic (i. e., equally-spaced) inspection and Type I censoring. Under the periodic inspection, the exact sampling distribution of maximum likelihood (ML) estimator of mean can not be derived. Hence sample size and acceptance criterion are determined by the algorithm proposed on the basis of Monte Carlo simulation such that the producer's and consumer's risks are satisfied for given censoring time and number of inspections. In addition, the developed RASP is compared in terms of sampling size, OC curve, and expected completion time. The effects for the RASP by the chosen inspection scheme are also discussed.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.1055-1066
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• 2009

Many articles have considered a hybrid censoring scheme, which is a mixture of Type-I and Type-II censoring schemes. We introduce a double hybrid censoring scheme and derive some approximate maximum likelihood estimators(AMLEs) of the scale parameter for the half logistic distribution under the proposed double hybrid censored samples. The scale parameter is estimated by approximate maximum likelihood estimation method using two different Taylor series expansion types. We also obtain the maximum likelihood estimator(MLE) and the least square estimator(LSE) of the scale parameter under the proposed double hybrid censored samples. We compare the proposed estimators in the sense of the mean squared error. The simulation procedure is repeated 10,000 times for the sample size n = 20(10)40 and various censored samples. The performances of the AMLEs and MLE are very similar in all aspects but the MLE and LSE have not a closed-form expression, some numerical method must be employed.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.445-451
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• 2013

We consider the estimators for the parameters of the exponential model with limited replacements under the type I censoring scheme. Also, we propose the desirable number of replacements to provide the similar effects in terms of the mean square errors.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1271-1277
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• 2012

In this paper, we propose an estimation method of the parameter in an exponential distribution based on a progressive Type I interval censored sample with semi-missing observation. The maximum likelihood estimator (MLE) of the parameter in the exponential distribution cannot be obtained explicitly because the intervals are not equal in length under the progressive Type I interval censored sample with semi-missing data. To obtain the MLE of the parameter for the sampling scheme, we propose a method by which progressive Type I interval censored sample with semi-missing data is converted to the progressive Type II interval censored sample. Consequently, the estimation procedures in the progressive Type II interval censored sample can be applied and we obtain the MLE of the parameter and survival function. It will be shown that the obtained estimators have good performance in terms of the mean square error (MSE) and mean integrated square error (MISE).

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.457-465
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• 2005

We consider the estimation of parameter in the exponential model in the case that the number of replacements of failed items is limited. And the desirable number of replacements to give the similar effect as unlimited case in terms of the mean square errors is proposed.

• International Journal of Reliability and Applications
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• v.18 no.2
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• pp.21-44
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• 2017

Accelerated life tests (ALTs) are frequently used in manufacturing industries to evaluate the reliability of products within a reasonable amount of time and cost. Test units are subjected to elevated stresses which yield quick failures. Most of the previous works on designing ALT plans are focused on tests that involve a single stress. Many times more than one stress factor influence the product's functioning. This paper deals with the design of optimum modified ramp-stress ALT plan for Burr type XII distribution with Type-I censoring under two stress factors, viz., voltage and switching rate each at two levels- low and high. It is assumed that usage time to failure is power law function of switching rate, and voltage increases linearly with time according to modified ramp-stress scheme. The cumulative exposure model is used to incorporate the effect of changing stresses. The optimum plan is devised using D-optimality criterion wherein the ${\log}_{10}$ of the determinant of Fisher information matrix is maximized. The method developed has been explained using a numerical example and sensitivity carried out.

• Journal of Korean Society for Quality Management
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• v.24 no.2
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• pp.25-43
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• 1996

This paper presents the optimal and practical constant-stress accelerated life test plans for the lognormal lifetime distribution tinder assumptions of intermittent inspection and Type-I censoring. In an optimal plan, the low stress level and the proportions of test units allocated at each stress are determined under given inspection scheme and number of inspections such that the asymptotic variance of the maximum likelihood estimator of a certain quantile at use condition is minimized. Although the practical plan adopts the same design criterion, it involves three rather than two overstress levels in order to compromise the practical deficiencies of the optimal plan. Computational experiments are conducted to choose an allocation plan and a inspection scheme of the practical plan and to compare with test plans over a range of parameter values.