• Title/Summary/Keyword: interval censored

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Confidence Intervals and Joint Confidence Regions for the Two-Parameter Exponential Distribution based on Records

  • Asgharzadeh, A.;Abdi, M.
    • Communications for Statistical Applications and Methods
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    • v.18 no.1
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    • pp.103-110
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    • 2011
  • Exponential distribution is widely adopted as a lifetime model. Many authors have considered the interval estimation of the parameters of two-parameter exponential distribution based on complete and censored samples. In this paper, we consider the interval estimation of the location and scale parameters and the joint confidence region of the parameters of two-parameter exponential distribution based on upper records. A simulation study is done for the performance of all proposed confidence intervals and regions. We also propose the predictive intervals of the future records. Finally, a numerical example is given to illustrate the proposed methods.

Classical and Bayesian studies for a new lifetime model in presence of type-II censoring

  • Goyal, Teena;Rai, Piyush K;Maury, Sandeep K
    • Communications for Statistical Applications and Methods
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    • v.26 no.4
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    • pp.385-410
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    • 2019
  • This paper proposes a new class of distribution using the concept of exponentiated of distribution function that provides a more flexible model to the baseline model. It also proposes a new lifetime distribution with different types of hazard rates such as decreasing, increasing and bathtub. After studying some basic statistical properties and parameter estimation procedure in case of complete sample observation, we have studied point and interval estimation procedures in presence of type-II censored samples under a classical as well as Bayesian paradigm. In the Bayesian paradigm, we considered a Gibbs sampler under Metropolis-Hasting for estimation under two different loss functions. After simulation studies, three different real datasets having various nature are considered for showing the suitability of the proposed model.

A HYPOTHESIS TESTING PROCEDURE OF ASSESSMENT FOR THE LIFETIME PERFORMANCE INDEX UNDER A GENERAL CLASS OF INVERSE EXPONENTIATED DISTRIBUTIONS WITH PROGRESSIVE TYPE I INTERVAL CENSORING

  • KAYAL, TANMAY;TRIPATHI, YOGESH MANI;WU, SHU-FEI
    • Journal of applied mathematics & informatics
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    • v.37 no.1_2
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    • pp.105-121
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    • 2019
  • One of the main objective of manufacturing industries is to assess the capability performance of different processes. In this paper, we use the lifetime performance index $C_L$ as a criterion to measure larger-the-better type quality characteristic for evaluating the product performance. The lifetimes of products are assumed to follow a general class of inverted exponentiated distributions. We use maximum likelihood estimator to estimate the lifetime performance index under the assumption that data are progressive type I interval censored. We also obtain asymptotic distribution of this estimator. Based on this estimator, a new hypothesis testing procedure is developed with respect to a given lower specification limit. Finally, two numerical examples are discussed in support of the proposed testing procedure.

Different penalty methods for assessing interval from first to successful insemination in Japanese Black heifers

  • Setiaji, Asep;Oikawa, Takuro
    • Asian-Australasian Journal of Animal Sciences
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    • v.32 no.9
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    • pp.1349-1354
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    • 2019
  • Objective: The objective of this study was to determine the best approach for handling missing records of first to successful insemination (FS) in Japanese Black heifers. Methods: Of a total of 2,367 records of heifers born between 2003 and 2015 used, 206 (8.7%) of open heifers were missing. Four penalty methods based on the number of inseminations were set as follows: C1, FS average according to the number of inseminations; C2, constant number of days, 359; C3, maximum number of FS days to each insemination; and C4, average of FS at the last insemination and FS of C2. C5 was generated by adding a constant number (21 d) to the highest number of FS days in each contemporary group. The bootstrap method was used to compare among the 5 methods in terms of bias, mean squared error (MSE) and coefficient of correlation between estimated breeding value (EBV) of non-censored data and censored data. Three percentages (5%, 10%, and 15%) were investigated using the random censoring scheme. The univariate animal model was used to conduct genetic analysis. Results: Heritability of FS in non-censored data was $0.012{\pm}0.016$, slightly lower than the average estimate from the five penalty methods. C1, C2, and C3 showed lower standard errors of estimated heritability but demonstrated inconsistent results for different percentages of missing records. C4 showed moderate standard errors but more stable ones for all percentages of the missing records, whereas C5 showed the highest standard errors compared with noncensored data. The MSE in C4 heritability was $0.633{\times}10^{-4}$, $0.879{\times}10^{-4}$, $0.876{\times}10^{-4}$ and $0.866{\times}10^{-4}$ for 5%, 8.7%, 10%, and 15%, respectively, of the missing records. Thus, C4 showed the lowest and the most stable MSE of heritability; the coefficient of correlation for EBV was 0.88; 0.93 and 0.90 for heifer, sire and dam, respectively. Conclusion: C4 demonstrated the highest positive correlation with the non-censored data set and was consistent within different percentages of the missing records. We concluded that C4 was the best penalty method for missing records due to the stable value of estimated parameters and the highest coefficient of correlation.

Additive hazards models for interval-censored semi-competing risks data with missing intermediate events (결측되었거나 구간중도절단된 중간사건을 가진 준경쟁적위험 자료에 대한 가산위험모형)

  • Kim, Jayoun;Kim, Jinheum
    • The Korean Journal of Applied Statistics
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    • v.30 no.4
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    • pp.539-553
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    • 2017
  • We propose a multi-state model to analyze semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the three states of the illness-death model: healthy, disease, and dead. The 'diseased' state can be considered as the intermediate event. Two more states are added into the illness-death model to incorporate the missing events, which are caused by a loss of follow-up before the end of a study. One of them is a state of the lost-to-follow-up (LTF), and the other is an unobservable state that represents an intermediate event experienced after the occurrence of LTF. Given covariates, we employ the Lin and Ying additive hazards model with log-normal frailty and construct a conditional likelihood to estimate transition intensities between states in the multi-state model. A marginalization of the full likelihood is completed using adaptive importance sampling, and the optimal solution of the regression parameters is achieved through an iterative quasi-Newton algorithm. Simulation studies are performed to investigate the finite-sample performance of the proposed estimation method in terms of empirical coverage probability of true regression parameters. Our proposed method is also illustrated with a dataset adapted from Helmer et al. (2001).

Estimation of Mean Residual Life Function for a Coherent System (코히어런트 시스템에서 평균잔여수명함수(平均殘餘壽命函數)의 추정(推定))

  • Park, Byung-Gu
    • Journal of the Korean Data and Information Science Society
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    • v.4
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    • pp.97-107
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    • 1993
  • In this paper we propose a nonparametric estimator of the men residual life function (MRLF) on a coherent system under the condition that the component lifetimes are censored by system lifetime. It is shown that the proposed estimator, considered as a function of age t, converges weakly to a Gaussian process on a fixed interval. A consistent estimator of asymptotic variance of the proposed estimator is also given.

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가속수명시험을 통한 신뢰성보험요율 추정 - 합금무계목인발강관의 사례를 중심으로 -

  • Hong, Yeon-Ung;Jeong, Yeong-Hun
    • 한국데이터정보과학회:학술대회논문집
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    • 2004.04a
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    • pp.1-5
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    • 2004
  • In this paper, we calculate the premium rate of reliability insurance policy for T11 composite metreial under the assumption of Weibull physics of failure and Arrhenius law. We also describe the performance factors which have an effect on failure characteristics of wiper motors. The maximum likelihood estimates of shape parameter and scale parameter are obtained by using interval censored real data of sample sizes 6 using MINITAB.

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On Estimating Burr Type XII Parameter Based on General Type II Progressive Censoring

  • Kim Chan-Soo
    • Communications for Statistical Applications and Methods
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    • v.13 no.1
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    • pp.89-99
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    • 2006
  • This article deals with the problem of estimating parameters of Burr Type XII distribution, on the basis of a general progressive Type II censored sample using Bayesian viewpoints. The maximum likelihood estimator does not admit closed form but explicit sharp lower and upper bounds are provided. Assuming squared error loss and linex loss functions, Bayes estimators of the parameter k, the reliability function, and the failure rate function are obtained in closed form. Finally, a simulation study is also included.

Bootstrap Confidence Intervals for an Adjusted Survivor Function under the Dependent Censoring Model

  • Lee, Seung-Yeoun;Sok, Yong-U
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.127-135
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    • 2001
  • In this paper, we consider a simple method for testing the assumption of independent censoring on the basis of a Cox proportional hazards regression model with a time-dependent covariate. This method involves a two-stage sampling in which a random subset of censored observations is selected and followed-up until their true survival times are observed. Lee and Wolfe(1998) proposed an adjusted estimate of the survivor function for the dependent censoring under a proportional hazards alternative. This paper extends their result to obtain a bootstrap confidence interval for the adjusted survivor function under the dependent censoring. The proposed procedure is illustrated with an example of a clinical trial for lung cancer analysed in Lee and Wolfe(1998).

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A Distribution-Free Confidence Interval for Difference between Treatment and Control

  • Park, Sang-Gue;Kim, Tai-Kyoo;Jeong, Gyu-Jin;Yoon, Bae-Hyun
    • Journal of Korean Society for Quality Management
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    • v.18 no.1
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    • pp.40-47
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    • 1990
  • The two-sample problem where an experimental treatment is compared with a control is considered. Without making any parametric-model assumptions for the distributions(or survival distributions), a measure for summarizing the differences between the treatment and the control is introduced. A method for constructing a confidence interval for the proposed measure is given in cases of complete and right random censored data. This method is illustrated with two numerical examples.

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