• Journal of the Korean Data and Information Science Society
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• 제19권3호
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• pp.951-957
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• 2008

We derive some approximate maximum likelihood estimators(AMLEs) and maximum likelihood estimator(MLE) of the scale parameter in the half-triangle distribution based on progressively Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples. We also obtain the approximate maximum likelihood estimators of the reliability function using the proposed estimators. We compare the proposed estimators in the sense of the mean squared error.

• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.367-376
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• 2003

Two explicit estimators of the scale parameter in an exponential distribution based on Type-II censored samples are proposed by appropriately approximating the likelihood function. Then two type tests, including the modified Cramer-von Mises test and Kolmogorov-Smirnov test are developed for the exponential distribution based on Type-II censored samples by using the proposed estimators. For each test, Monte Carlo techniques are used to generate critical values. The powers of these tests are investigated under several alternative distributions.

• Communications for Statistical Applications and Methods
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• 제21권1호
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• pp.93-103
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• 2014

This paper deals with the problem of predicting censored data in a half triangle distribution with an unknown parameter based on progressively Type-II censored samples. We derive maximum likelihood predictors and some approximate maximum likelihood predictors of censored failure times in a progressively Type-II censoring scheme. In addition, we construct the shortest-length predictive intervals for censored failure times. Finally, Monte Carlo simulations are used to assess the validity of the proposed methods.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2006년도 PROCEEDINGS OF JOINT CONFERENCEOF KDISS AND KDAS
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• pp.279-293
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• 2006

In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and location parameter of the exponential distribution based on multiply Type-II censored samples. Then three type tests, including the modified Clamor-von Mises test, the modified Watson test and the modified Kolmogorov-Smirnov test are developed for the exponential distribution based on multiply Type-II censored samples by using the proposed estimators. For each test, Monte Carlo techniques are used to generate critical values. The powers of these tests are investigated under several alternative distributions.

• Journal of the Korean Data and Information Science Society
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• 제21권2호
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• pp.317-325
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• 2010

In this paper, we develop four modified empirical distribution function (EDF) type tests using approximate maximum likelihood estimators for the half-logistic distribution based on multiply Type-II censored samples. We also propose modified normalize sample Lorenz curve polt and new test statistics. We compare the above test statistics in the sense of the power for various censored samples. We present an example to illustrate this method.

• Journal of the Korean Data and Information Science Society
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• 제25권3호
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• pp.633-641
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• 2014

The exponential distibution is one of the most popular distributions in analyzing the lifetime data. In this paper, we propose multiply Type I hybrid censoring. And this paper presents the statistical inference on the scale parameter for the exponential distribution when samples are multiply Type I hybrid censoring. The scale parameter is estimated by approximate maximum likelihood estimation methods using two different Taylor series expansion types ($AMLE_I$, $AMLE_{II}$). We also obtain the maximum likelihood estimator (MLE) of the scale parameter ${\sigma}$ under the proposed multiply Type I hybrid censored samples. 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 $AMLE_{II}$ is better than $AMLE_I$ in the sense of the RMSE.

• Journal of the Korean Data and Information Science Society
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• 제20권4호
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• pp.719-731
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• 2009

This paper deals with properties of the exponentiated extreme value distribution. We derive the approximate maximum likelihood estimators of the scale parameter and location parameter of the exponentiated extreme value distribution based on multiply Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples.

• Communications for Statistical Applications and Methods
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• 제13권3호
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• pp.537-550
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• 2006

In this paper, we develope three modified empirical distribution function type tests, the modified Cramer-von Mises test, the modified Anderson-Darling test, and the modified Kolmogorov-Smirnov test for the two-parameter exponential distribution with unknown parameters based on multiply Type-II censored samples. For each test, Monte Carlo techniques are used to generate the critical values. The powers of these tests are also investigated under several alternative distributions.

• Communications for Statistical Applications and Methods
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• 제16권2호
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• pp.349-361
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• 2009

In this paper, we derive the approximate maximum likelihood estimators of the shape parameter and the scale parameter in a Weibull distribution under multiply Type-II censoring by the approximate maximum likelihood estimation method. We develop three modified empirical distribution function type tests for the Weibull distribution based on multiply Type-II censored samples. We also propose modified normalized sample Lorenz curve plot and new test statistic.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2004년도 춘계학술대회
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• pp.203-210
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• 2004

When the available sample is multiply Type-II censored, the maximum likelihood estimators of the location and the scale parameters of two- parameter exponential distribution do not admit explicitly. In this case, we propose some estimators which are linear functions of the order statistics and also propose some estimators by approximating the likelihood equations appropriately. We compare the proposed estimators by the mean squared errors.