• Title/Summary/Keyword: type II censoring

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Goodness-of-fit Test for the Weibull Distribution Based on Multiply Type-II Censored Samples

  • Kang, Suk-Bok;Han, Jun-Tae
    • Communications for Statistical Applications and Methods
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    • v.16 no.2
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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.

Predictions for Progressively Type-II Censored Failure Times from the Half Triangle Distribution

  • Seo, Jung-In;Kang, Suk-Bok
    • Communications for Statistical Applications and Methods
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    • v.21 no.1
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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.

AMLEs for Rayleigh Distribution Based on Progressive Type-II Censored Data

  • Seo, Eun-Hyung;Kang, Suk-Bok
    • Communications for Statistical Applications and Methods
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    • v.14 no.2
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    • pp.329-344
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    • 2007
  • In this paper, we shall propose the AMLEs of the scale parameter and the location parameter in the two-parameter Rayleigh distribution based on progressive Type-II censored samples when one parameter is known. We also propose the AMLEs of the two parameters in the Rayleigh distribution based on progressive Type-II censored samples when two parameters are unknown. We simulate the mean squared errors of the proposed estimators through Monte Carlo simulation for various censoring schemes.

Accelerated Life Test Plans Based on Small Sample Property

  • Yun, Won Young
    • Journal of Korean Society for Quality Management
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    • v.23 no.1
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    • pp.41-49
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    • 1995
  • This paper suggests optimal accelerated constant stress life tests in Exponential distribution. The relationship between the log-mean life and the loaded stress is assumed to be linear. Optimal plans considering mean square errors of maximum likelihood estimators of the log mean life and test costs are obtained. We consider accelerated life tests with two stress levels, and as data types, failure censoring( type II) and time censoring(type I) data are used. We propose the procedure to obtain the optimal plans for each case. Some examples are also included.

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Approximate MLEs for Exponential Distribution Under Multiple Type-II Censoring

  • Kang, Suk-Bok
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.4
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    • pp.983-988
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    • 2003
  • 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 approximate maximum likelihood estimators by approximating the likelihood equations appropriately. We present an example to illustrate these estimation methods.

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Bayesian Inference for the Two-Parameter Exponential Models : Type-II Censored Case

  • Sohn, Joong-Kweon;Kim, Heon-Joo
    • Journal of the Korean Statistical Society
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    • v.24 no.2
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    • pp.313-335
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    • 1995
  • Suppose that we have $k(k \geq 2)$ populations (or systems), say $\pi_1, \cdots, \pi_k$, to be tested. Under the type-II censored testing without replacement we consider the problem of estimating the unknown parameters of interests and the reliability for a given time t for each population. Also we compare the perfomances of the proposed Bayes estimators with another estiamtors under the Jeffrey-type noninformative prior distribution.

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Estimation for the Half-Triangle Distribution Based on Progressively Type-II Censored Samples

  • Han, Jun-Tae;Kang, Suk-Bok
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.3
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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.

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Estimation for the Rayleigh Distribution with Known Parameter under Multiply Type-II Censoring

  • Han, Jun-Tae;Kang, Suk-Bok
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.3
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    • pp.933-943
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    • 2006
  • For multiply Type-II censored samples from two-parameter Rayleigh distribution, we derive some approximate maximum likelihood estimators of parameter in the Rayleigh distribution when the other parameter is known. We also compare the proposed estimators in the sense of the mean squared error for various censored samples.

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Estimation for the Generalized Extreme Value Distribution Based on Multiply Type-II Censored Samples

  • Han, Jun-Tae;Kang, Suk-Bok
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.3
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    • pp.817-826
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    • 2007
  • In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and the location parameter in a generalized extreme value distribution under multiply Type-II censoring by the approximate maximum likelihood estimation method. We compare the proposed estimators in the sense of the mean squared error for various censored samples.

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Estimation for the Half Logistic Distribution Based on Double Hybrid Censored Samples

  • Kang, Suk-Bok;Cho, Young-Seuk;Han, Jun-Tae
    • 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.