• 제목/요약/키워드: Censored Data

검색결과 405건 처리시간 0.021초

Estimation for Exponential Distribution Under Multiple Type-II Censoring

  • 강석복;류세기
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2003년도 추계학술대회
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    • pp.13-18
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    • 2003
  • When the available sample is multiply type-II censored, the maximum likelihood estimators of the location and scale parameters of two- parameter exponential distribution do not exist explicitly. In this case, we propose several approximate maximum likelihood estimators by approximating the likelihood equations appropriately. We present an example to illustrate these estimation methods.

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Estimation of P(X

  • Kil Ho Cho;Jang Sik Cho;Young Joon Cha;Jae Man Lee
    • Communications for Statistical Applications and Methods
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    • 제3권3호
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    • pp.253-261
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    • 1996
  • In this paper, we derive the maximum likelihood estimator of P=P(X

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Nonparametric Bayesian Estimation for the Exponential Lifetime Data under the Type II Censoring

  • Lee, Woo-Dong;Kim, Dal-Ho;Kang, Sang-Gil
    • Communications for Statistical Applications and Methods
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    • 제8권2호
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    • pp.417-426
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    • 2001
  • This paper addresses the nonparametric Bayesian estimation for the exponential populations under type II censoring. The Dirichlet process prior is used to provide nonparametric Bayesian estimates of parameters of exponential populations. In the past, there have been computational difficulties with nonparametric Bayesian problems. This paper solves these difficulties by a Gibbs sampler algorithm. This procedure is applied to a real example and is compared with a classical estimator.

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Acceptance Sampling Plans in the Rayleigh Model

  • Baklizi Ayman;El-Masri Abedel-Qader;AL-Nasser Amjad
    • Communications for Statistical Applications and Methods
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    • 제12권1호
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    • pp.11-18
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    • 2005
  • Assume that the life times of the units under test follow the Rayleigh distribution and the test is terminated at a pre assigned time. Acceptance sampling plans are developed for this situation. The minimum sample size necessary to ensure the specified average life are obtained and the operating characteristic values of the sampling plans and producer's risk are given. An example is given to illustrate the methodology.

Survival Function Estimation for the Proportional Hazards Regression Model

  • Cha, Young Joon
    • 품질경영학회지
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    • 제18권1호
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    • pp.9-20
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    • 1990
  • The purpose of this paper is to propose the modified semiparametric estimators for survival function in the Cox's regression model with randomly censored data based on Tsiatis and Breslow estimators, and present their asymptotic variances estimates. The proposed estimators are compared to Tsiatis, Breslow, and Kaplan-Meier estimators through a small-sample Monte Carlo study. The simulation results show that the proposed estimators are preferred for small sample sizes.

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Bayesian Prediction of Exponentiated Weibull Distribution based on Progressive Type II Censoring

  • Jung, Jinhyouk;Chung, Younshik
    • Communications for Statistical Applications and Methods
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    • 제20권6호
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    • pp.427-438
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    • 2013
  • Based on progressive Type II censored sampling which is an important method to obtain failure data in a lifetime study, we suggest a very general form of Bayesian prediction bounds from two parameters exponentiated Weibull distribution using the proper general prior density. For this, Markov chain Monte Carlo approach is considered and we also provide a simulation study.

On Characterizing Distributions by Some Properties of the Distribution Truncated at the rth order Statistic

  • Sangun Park
    • Communications for Statistical Applications and Methods
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    • 제1권1호
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    • pp.52-56
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    • 1994
  • When we have an i.i.d. sample of size n from a continuous distribution, the distribution truncated on the left at the rth order statistic plays an important role in the theoretical analysis of the Type 2 censored data. The charaterization of distributions by the average of the conditional expectation and the average of the conditional information concerning the truncated distribution is studied here.

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BAYESIAN AND CLASSICAL INFERENCE FOR TOPP-LEONE INVERSE WEIBULL DISTRIBUTION BASED ON TYPE-II CENSORED DATA

  • ZAHRA SHOKOOH GHAZANI
    • Journal of applied mathematics & informatics
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    • 제42권4호
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    • pp.819-829
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    • 2024
  • This paper delves into an examination of both non-Bayesian and Bayesian estimation techniques for determining the Topp-leone inverse Weibull distribution parameters based on progressive Type-II censoring. The first approach employs expectation maximization (EM) algorithms to derive maximum likelihood estimates for these variables. Subsequently, Bayesian estimators are obtained by utilizing symmetric and asymmetric loss functions such as Squared error and Linex loss functions. The Markov chain Monte Carlo method is invoked to obtain these Bayesian estimates, solidifying their reliability in this framework.

피로곡선 모형의 통계적 분석 및 비교 (Statistical Analysis and Comparison of Fatigue Curve Models)

  • 서순근;조유희
    • 품질경영학회지
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    • 제31권2호
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    • pp.165-182
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    • 2003
  • The fatigue has been considered to the most important failure mode where optimal design or reliability prediction of the machinery in aircraft, atomic reactors, and structure systems, etc., is required. When the statistical analysis of fatigue life data is performed, some difficulties are present because of the following facts : nonlinear relationship, heteroscedastic data, large scatter in the data, censored data (runouts), and existence of fatigue limit. To find the S-N curve models that characterize fatigue strength better, this research compares existing fatigue curve models developed recently in terms of the residual mean square and the estimate of fatigue limit, etc. for various fatigue data sets.

Maximum penalized likelihood estimation for a stress-strength reliability model using complete and incomplete data

  • Hassan, Marwa Khalil
    • Communications for Statistical Applications and Methods
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    • 제25권4호
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    • pp.355-371
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    • 2018
  • The two parameter negative exponential distribution has many practical applications in queuing theory such as the service times of agents in system, the time it takes before your next telephone call, the time until a radioactive practical decays, the distance between mutations on a DNA strand, and the extreme values of annual snowfall or rainfall; consequently, has many applications in reliability systems. This paper considers an estimation problem of stress-strength model with two parameter negative parameter exponential distribution. We introduce a maximum penalized likelihood method, Bayes estimator using Lindley approximation to estimate stress-strength model and compare the proposed estimators with regular maximum likelihood estimator for complete data. We also introduce a maximum penalized likelihood method, Bayes estimator using a Markov chain Mote Carlo technique for incomplete data. A Monte Carlo simulation study is performed to compare stress-strength model estimates. Real data is used as a practical application of the proposed model.