• 제목/요약/키워드: Censoring distribution

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Estimation of Failure Rate and Acceleration Factor in Accelerated Life Testing under Type-I Censoring (정시중단 가속수명시험에서 고장률과 가속계수의 추정)

  • Kong, Myung Bock;Park, Il Gwang
    • Journal of Korean Institute of Industrial Engineers
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    • 제29권2호
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    • pp.145-149
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    • 2003
  • We consider the estimation of failure rate and acceleration factor under type-I censoring without using acceleration model when testing is conducted in only one highly accelerated condition. Failure times of an item are assumed to be exponentially distributed. It is also assumed that the uncertainty about the acceleration factor, the failure time contraction ratio between accelerated condition and use condition, can be modeled by the uniform or gamma prior distribution of appropriate parameters. We respectively use Bayes and maximum likelihood approaches to estimate acceleration factor and failure rate in the use condition. An example is given to show how the method can be applied.

Mixed Replacement Designs for Life Testing with Interval Censoring

  • Tai Sup;kesar Singh
    • Communications for Statistical Applications and Methods
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    • 제6권2호
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    • pp.443-456
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    • 1999
  • The estimation of mean lifetimes in presence of interval censoring with mixed replacement procedure are examined when the distribution s of lifetimes are exponential. it is assumed that due to physical restrictions and/or economic constraints the number of failures is investigated only at several inspection times during the lifetime test; thus there is interval censoring. Comparisons of mixed replacement designs are made with those with and without replacement The maximum likelihood estimator is found in an implicit form. The Cramer-Rao lower bound which is the asymptotic variance of the estimator is derived. The test conditions for minimizing the Cramer-Rao lower bound and minimizing the test costs within a desired width of the Cramer-Rao bound have been studied.

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Estimation of the time-dependent AUC for cure rate model with covariate dependent censoring

  • Yang-Jin Kim
    • Communications for Statistical Applications and Methods
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    • 제31권4호
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    • pp.365-375
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    • 2024
  • Diverse methods to evaluate the prediction model of a time to event have been proposed in the context of right censored data where all subjects are subject to be susceptible. A time-dependent AUC (area under curve) measures the predictive ability of a marker based on case group and control one which are varying over time. When a substantial portion of subjects are event-free, a population consists of a susceptible group and a cured one. An uncertain curability of censored subjects makes it difficult to define both case group and control one. In this paper, our goal is to propose a time-dependent AUC for a cure rate model when a censoring distribution is related with covariates. A class of inverse probability of censoring weighted (IPCW) AUC estimators is proposed to adjust the possible sampling bias. We evaluate the finite sample performance of the suggested methods with diverse simulation schemes and the application to the melanoma dataset is presented to compare with other methods.

Analysis of generalized progressive hybrid censored competing risks data

  • Lee, Kyeong-Jun;Lee, Jae-Ik;Park, Chan-Keun
    • Journal of Advanced Marine Engineering and Technology
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    • 제40권2호
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    • pp.131-137
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    • 2016
  • In reliability analysis, it is quite common for the failure of any individual or item to be attributable to more than one cause. Moreover, observed data are often censored. Recently, progressive hybrid censoring schemes have become quite popular in life-testing problems and reliability analysis. However, a limitation of the progressive hybrid censoring scheme is that it cannot be applied when few failures occur before time T. Therefore, generalized progressive hybrid censoring schemes have been introduced. In this article, we derive the likelihood inference of the unknown parameters under the assumptions that the lifetime distributions of different causes are independent and exponentially distributed. We obtain the maximum likelihood estimators of the unknown parameters in exact forms. Asymptotic confidence intervals are also proposed. Bayes estimates and credible intervals of the unknown parameters are obtained under the assumption of gamma priors on the unknown parameters. Different methods are compared using Monte Carlo simulations. One real data set is analyzed for illustrative purposes.

Goodness of Fit Tests for the Exponential Distribution based on Multiply Progressive Censored Data (다중 점진적 중도절단에서 지수분포의 적합도 검정)

  • Yun, Hyejeong;Lee, Kyeongjun
    • Journal of the Korean Data Analysis Society
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    • 제20권6호
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    • pp.2813-2827
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    • 2018
  • Progressive censoring schemes have become quite popular in reliability study. Under progressive censored data, however, some units can be failed between two points of observation with exact times of failure of these units unobserved. For example, loss may arise in life-testing experiments when the failure times of some units were not observed due to mechanical or experimental difficulties. Therefore, multiply progressive censoring scheme was introduced. So, we derives a maximum likelihood estimator of the parameter of exponential distribution. And we introduced the goodness-of-fit test statistics using order statistic and Lorenz curve. We carried out Monte Carlo simulation to compare the proposed test statistics. In addition, real data set have been analysed. In Weibull and chi-squared distributions, the test statistics using Lorenz curve are more powerful than test statistics using order statistics.

Use of Lèvy distribution to analyze longitudinal data with asymmetric distribution and presence of left censored data

  • Achcar, Jorge A.;Coelho-Barros, Emilio A.;Cuevas, Jose Rafael Tovar;Mazucheli, Josmar
    • Communications for Statistical Applications and Methods
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    • 제25권1호
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    • pp.43-60
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    • 2018
  • This paper considers the use of classical and Bayesian inference methods to analyze data generated by variables whose natural behavior can be modeled using asymmetric distributions in the presence of left censoring. Our approach used a $L{\grave{e}}vy$ distribution in the presence of left censored data and covariates. This distribution could be a good alternative to model data with asymmetric behavior in many applications as lifetime data for instance, especially in engineering applications and health research, when some observations are large in comparison to other ones and standard distributions commonly used to model asymmetry data like the exponential, Weibull or log-logistic are not appropriate to be fitted by the data. Inferences for the parameters of the proposed model under a classical inference approach are obtained using a maximum likelihood estimators (MLEs) approach and usual asymptotical normality for MLEs based on the Fisher information measure. Under a Bayesian approach, the posterior summaries of interest are obtained using standard Markov chain Monte Carlo simulation methods and available software like SAS. A numerical illustration is presented considering data of thyroglobulin levels present in a group of individuals with differentiated cancer of thyroid.

New Accelerated Life Test Plans for Weibull and Lognormal Lifetime Distributions (와이블과 대수정규 수명분포를 따를 때 새로운 가속수명시험 계획의 개발)

  • Seo, Sun-Keun
    • Journal of Applied Reliability
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    • 제14권3호
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    • pp.182-190
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    • 2014
  • This paper presents new practical accelerated life test plans with different censoring times at three levels of stress for Weibull and lognormal lifetime distributions, respectively. The proposed plans are compared with the corresponding two-level statistically optimal plans and three-level compromise and practical plans. Computational results indicate that new practical plans have been more precise and effective than the existing three-level plans under a constraint of total testing time. In addition, a procedure to determine useful ALT plans is illustrated with a numerical example.

Empirical Bayes Nonparametric Estimation with Beta Processes Based on Censored Observations

  • Hong, Jee-Chang;Kim, Yongdai;Inha Jung
    • Journal of the Korean Statistical Society
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    • 제30권3호
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    • pp.481-498
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    • 2001
  • Empirical Bayes procedure of nonparametric estiamtion of cumulative hazard rates based on censored data is considered using the beta process priors of Hjort(1990). Beta process priors with unknown parameters are used for cumulative hazard rates. Empirical Bayes estimators are suggested and asymptotic optimality is proved. Our result generalizes that of Susarla and Van Ryzin(1978) in the sensor that (i) the cumulative hazard rate induced by a Dirichlet process is a beta process, (ii) our empirical Bayes estimator does not depend on the censoring distribution while that of Susarla and Van Ryzin(1978) does, (iii) a class of estimators of the hyperprameters is suggested in the prior distribution which is assumed known in advance in Susarla and Van Ryzin(1978). This extension makes the proposed empirical Bayes procedure more applicable to real dta sets.

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Optimal Design of Accelerated Life Tests under Model Uncertainty (불확정 모형하에서 가속수명시험의 최적 설계)

  • 서순근;하천수;김갑석
    • Journal of Korean Society for Quality Management
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    • 제29권3호
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    • pp.49-65
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    • 2001
  • This paper presents new compromise ALT plan which is applied to situations that true relationship between stress and parameters is not known exactly. The assumed failure distribution of this study is one of location-scale family, i. e., exponential, Weibull, and lognormal distributions which have been ones of the popular choices of failure distributions. The method of applying the stress is constant, and the censoring mechanism is Type I censoring. Compared with existing compromise plans under true simple linear model in terms of statistical efficiency, the efficiency of new compromise plan is better than the corresponding other compromise ones in most cases. For case when true model is quadratic, this plan can be used without any severe loss in statistical efficiency. The proposed new compromise ALT plan is illustrated with a numerical example and sensitivity analyses are conducted to study effects of pre-estimates of design parameters.

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Design of Accelerated Life Test Sampling Plans for Exponential Distribution under Type II Censoring (지수수명분포에 대한 가속수명시험 샘플링검사방식의 설계: 제II종 관측중단의 경우)

  • Chun, Young Rok
    • Journal of Korean Society for Quality Management
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    • 제23권4호
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    • pp.13-27
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    • 1995
  • This paper considers the design of life test sampling plans based on Type II censored accelerated life tests. The lifetime distribution of products is assumed to be exponential. An estimator of acceleration factor between use condition stress and an accelerated level of stress higher than use condition stress is assumed to be known. The critical value for lot acceptance and the number of failure before censoring which satisfy the producer's and consumer's risk requirements are determined. The properties of the proposed life test sampling plans are investigated.

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