• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.789-798
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• 2000

The mean residual function is the expected remaining life of an item at age x. The problem of trend change in the mean residual life is great interest in the reliability and survival analysis. In this paper, we develop a family of test statistics for testing whether or not the mean residual life changes its trend. The asymptotic normality of the test statistics is established. Monte Carlo simulations are conducted to study the performance of our test statistics.

• International Journal of Reliability and Applications
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• v.3 no.2
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• pp.91-98
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• 2002

A class of life distributions, whose mean residual life keeps stable at its earlier phase and then starts to decrease in time, is proposed to model the life of an element haying survived its burn-in. A strongly consistent estimator and a nonparametric testing procedure are developed to locate the occurrence of the change-point of the mean residual life. Finally, some numerical simulations are employed to be an illustration as well.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.965-971
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• 2004

In this paper we consider several nonparametric estimators for the mean residual life by using the partial moment approximation under the proportional hazard model. Also we compare the magnitude of mean square error of the proposed nonparametric estimators for mean residual life under the proportional hazard model.

• Journal of Korean Society for Quality Management
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• v.26 no.4
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• pp.101-110
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• 1998

The mean residual life function is the expected remaining life of an item at age $\chi$. The problem of trend change in the mean residual life is great interest in the reliability and survival analysis. In this paper we develop a new test statistic for testing whether or not the mean residual life changes its trend based on a complete sample. Monte Carlo simulations are conducted to compare the perfor mance of our test statistic with that of previously known tests.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.93-101
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• 1995

We present a brief survey concerning the relations between mean residual life and failure rate. Change points of mean residual life and failure rate are known to be different in general and we explore such situations in this paper. A few parametric models which show bathtub-shaped failure rate are examined in details, including the shape of its corresponding mean residual life function. We give some graphical comparisons of trend changes of mean residual life and failure rate for various choices of parameters for each parametric model.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.225-230
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• 1997

We, in this paper, propose an estimator of mean residual life function by using the residual survival function under random censoring and prove the uniform consistency and weak convergence result of this estimator. Also an example is illustrated by the real data.

• Journal of the Korean Statistical Society
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• v.32 no.1
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• pp.25-32
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• 2003

In this paper, we define the mean life process for the right censored data and show the asymptotic equivalence between two kinds of the mean life processes. We use the Kaplan-Meier and Susarla-Van Ryzin estimates as the estimates of survival function for the construction of the mean life processes. Also we show the asymptotic equivalence between two mean residual life processes as an application and finally discuss some difficulties caused by the censoring mechanism.

• International Journal of Reliability and Applications
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• v.6 no.2
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• pp.79-85
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• 2005

We show how comparative mean residual life functions (MRL) can be used to give unique insights into strengths of materials data. Recall that Weibull's original reliability function was developed studying and fitting strengths for various materials. This creative comparing of MRL functions approach can be used for regular life data or any time to response data. We apply graphical MRL's to real data from tests of tensile strength of high quality engineered wood.

• Journal of the Korean Statistical Society
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• v.25 no.1
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• pp.133-144
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• 1996

We, in this paper, propose a nonparametric estimator of bivariate mean residual life function based on Lin and Ying's (1993) bivariate survival function estimator of paired failure times under univariate censoring and prove the uniform consistency and the weak convergence result of this estimator. Through Monte Carlo simulation, the performances of the proposed estimator are tabulated and are illustrated with the skin grafts data.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.99-109
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• 1997

The estimation procedure of mean residual life function has been placed an important role in the study of survival analysis. In this paper, the product limit estimator on left truncated and right censoring model is proposed with asymptotic properties. Also, the small sample properties are investigated through the Monte Carlo study and the proposed product limit type estimator is compared with ordinary Kaplan-Meier type estimator.