• Title/Summary/Keyword: type II censoring

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On the Use of Winsorized Mean for Truncated Family of Distributions under Type II Censoring

  • Nanthakumar, A.;Selvavel, K.;Ali, M.Masoom
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.1
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    • pp.147-156
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    • 2002
  • In this paper, we study the properties of the modified winsorized mean to estimate the mean of a two-truncation parameter population. Under some mild conditions, the estimator is found to be strongly consistent and asymptotically unbiased even though the sample is doubly type II censored.

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Bayes Estimation for the Rayleigh Failure Model

  • Ko, Jeong-Hwan;Kang, Sang-Gil;Shin, Jae-Kyoung
    • Journal of the Korean Data and Information Science Society
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    • v.9 no.2
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    • pp.227-235
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    • 1998
  • In this paper, we consider a hierarchical Bayes estimation of the parameter, the reliability and hazard rate function based on type-II censored samples from a Rayleigh failure model. Bayes calculations can be implemented easily by means of the Gibbs sampler. A numerical study is provided.

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Prediction Intervals for Proportional Hazard Rate Models Based on Progressively Type II Censored Samples

  • Asgharzadeh, A.;Valiollahi, R.
    • Communications for Statistical Applications and Methods
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    • v.17 no.1
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    • pp.99-106
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    • 2010
  • In this paper, we present two methods for obtaining prediction intervals for the times to failure of units censored in multiple stages in a progressively censored sample from proportional hazard rate models. A numerical example and a Monte Carlo simulation study are presented to illustrate the prediction methods.

Testing Two Exponential Means Based on the Bayesian Reference Criterion

  • Kim, Dal-Ho;Chung, Dae-Sik
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.3
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    • pp.677-687
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    • 2004
  • We consider the comparison of two one-parameter exponential distributions with the complete data as well as the type II censored data. We adapt Bayesian test procedure for nested hypothesis based on the Bayesian reference criterion. Specifically we derive the expression for the Bayesian reference criterion to solve our problem. Also we provide numerical examples using simulated data sets to illustrate our results.

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Goodness-of-fit tests for the inverse Weibull or extreme value distribution based on multiply type-II censored samples

  • Kang, Suk-Bok;Han, Jun-Tae;Seo, Yeon-Ju;Jeong, Jina
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.4
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    • pp.903-914
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    • 2014
  • The inverse Weibull distribution has been proposed as a model in the analysis of life testing data. Also, inverse Weibull distribution has been recently derived as a suitable model to describe degradation phenomena of mechanical components such as the dynamic components (pistons, crankshaft, etc.) of diesel engines. In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and the shape parameter in the inverse Weibull distribution under multiply type-II censoring. We also develop four modified empirical distribution function (EDF) type tests for the inverse Weibull or extreme value distribution based on multiply type-II censored samples. We also propose modified normalized sample Lorenz curve plot and new test statistic.

New approach for analysis of progressive Type-II censored data from the Pareto distribution

  • Seo, Jung-In;Kang, Suk-Bok;Kim, Ho-Yong
    • Communications for Statistical Applications and Methods
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    • v.25 no.5
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    • pp.569-575
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    • 2018
  • Pareto distribution is important to analyze data in actuarial sciences, reliability, finance, and climatology. In general, unknown parameters of the Pareto distribution are estimated based on the maximum likelihood method that may yield inadequate inference results for small sample sizes and high percent censored data. In this paper, a new approach based on the regression framework is proposed to estimate unknown parameters of the Pareto distribution under the progressive Type-II censoring scheme. The proposed method provides a new regression type estimator that employs the spacings of exponential progressive Type-II censored samples. In addition, the provided estimator is a consistent estimator with superior performance compared to maximum likelihood estimators in terms of the mean squared error and bias. The validity of the proposed method is assessed through Monte Carlo simulations and real data analysis.

Estimation in the exponential distribution under progressive Type I interval censoring with semi-missing data

  • Shin, Hyejung;Lee, Kwangho
    • 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).

Bayesian analysis of an exponentiated half-logistic distribution under progressively type-II censoring

  • Kang, Suk Bok;Seo, Jung In;Kim, Yongku
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1455-1464
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    • 2013
  • This paper develops maximum likelihood estimators (MLEs) of unknown parameters in an exponentiated half-logistic distribution based on a progressively type-II censored sample. We obtain approximate confidence intervals for the MLEs by using asymptotic variance and covariance matrices. Using importance sampling, we obtain Bayes estimators and corresponding credible intervals with the highest posterior density and Bayes predictive intervals for unknown parameters based on progressively type-II censored data from an exponentiated half logistic distribution. For illustration purposes, we examine the validity of the proposed estimation method by using real and simulated data.

Reliability Estimation for the Exponential Distribution under Multiply Type-II Censoring

  • Kang, Suk-Bok;Lee, Sang-Ki;Choi, Hui-Taeg
    • 한국데이터정보과학회:학술대회논문집
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    • 2005.10a
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    • pp.13-26
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    • 2005
  • 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. We compare the proposed estimators in the sense of the mean squared error for various censored samples. We also obtain the approximate maximum likelihood estimator (AMLE) of the reliability function by using the proposed estimators. And then we compare the proposed estimators in the sense of the mean squared error.

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Reliability Estimation in an Exponentiated Logistic Distribution under Multiply Type-II Censoring

  • Han, Jun-Tae;Kang, Suk-Bok;Cho, Young-Seuk
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.4
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    • pp.1081-1091
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    • 2007
  • In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and location parameter in an exponentiated logistic 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. We also propose and compare the estimators of the reliability function by using the proposed estimators of the parameters.

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