• Journal of Korean Society for Quality Management
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• v.25 no.4
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• pp.79-87
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• 1997

In this paper, we obtain maximum likelihood estimator(MLE) of a parallel system reliability for the Marshall and Olkin's bivariate exponential model with birariate type 1 consored data. The asymptotic normal distribution of the estimator is obtained. Also we construct an a, pp.oximate confidence interval for the reliability based on MLE. We present a numerical study for obtaining MLE and a, pp.oximate confidence interval of the reliability.

• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.917-927
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• 1997

Consider the confidence interval estimators of treatment effect when some of data to be analyzed are randomly censored, assuming two-sample location-shift model. Recently proposed PARK and PARK(1995) Estimators is discussed and a bootstrap estimator is proposed. This estimator is compared with other well-known estimators throught the simulation studies and recommendations about the use are made.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.571-578
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• 2003

In this paper, we consider two components system which have bivariate weibull model with bivariate type I censored data. We proposed maximum likelihood estimator and relative frequency estimator for the reliability of series system. Also, we construct approximate confidence intervals for the reliability based on the two proposed estimators. And we present a numerical study.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.347-353
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• 2004

We propose a simple nonparametric estimator of relative risk in the two sample case of the proportional hazards model for complete data. The asymptotic distribution of this estimator is derived using a functional equation. We obtain the asymptotic normality of the proposed estimator and compare with Begun's estimator by confidence interval through simulations.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.419-428
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• 2005

The screening test is increasingly being used for predicting future disease in the person screened and has raised concerns about reliability of the result of its procedure. We propose an improved estimator of the confidence interval for the positive predictive value(PPV) in screening test by simply taking inverse sinh transformation comparing to Gastwirth(1987) estimator and show its efficiency through the simulation study.

• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.189-197
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• 2001

The estimation of mean lifetimes in presence of interval censoring with mixed replacement procedure is examined when the distributions 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. The maximum likelihood estimator is found in an implicit form. The Cramor-Rao lower bound, which is the asymptotic variance of the estimator, is derived. The estimation of mean lifetimes for competing failures model has been expanded.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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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.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.643-653
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• 2014

In this paper, we propose some estimators for the extreme value distribution based on the interval method and mid-point approximation method from the progressive Type-I interval censored sample. Because log-likelihood function is a non-linear function, we use a Taylor series expansion to derive approximate likelihood equations. We compare the proposed estimators in terms of the mean squared error by using the Monte Carlo simulation.

• The Journal of the Acoustical Society of Korea
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• v.24 no.4E
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• pp.152-157
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• 2005

In this paper, a new data-aided joint phase and frequency estimator, which has very low computational complexity, is proposed and its variances of phase and frequency estimates are derived. To estimate the phase and frequency offset, first of all, the overall observation interval is divided into same length sub-intervals, and then phase estimates are independently computed based on symbols of the each sub-intervals. To be continue the sequence of computed phase estimates, proper integer multiples of $2{\pi}$ are added to (or subtracted from) the computed phase estimates, which is called linearized phase estimate. The phase offset of the proposed joint estimator is estimated by averaging the linearized phase estimates and the frequency offset by averaging the differences between consecutive linearized phase estimates. The variance of the proposed phase offset estimate is same to MCRB of phase if there is no frequency offset, but it is smaller than MCRB of phase if there is frequency offset. However, the variance of the proposed frequency offset estimate is bigger by at least 0.5 dB than MCRB of frequency with the same observation interval.