• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.501-509
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• 2009

Recently the interval estimation of binomial proportions is revisited in various literatures. This is mainly due to the erratic behavior of the coverage probability of the well-known Wald confidence interval. Various alternatives have been proposed. Among them, the Agresti-Coull confidence interval, the Wilson confidence interval and the Bayes confidence interval resulting from the noninformative Jefferys prior were recommended by Brown et al. (2001). However, unlike the binomial distribution case, little is known about the properties of the confidence intervals in finite population sampling. In this note, the property of confidence intervals is investigated in anile population sampling.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.898-902
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• 2018

A novel heart beat interval estimation algorithm is presented based on parabola approximation method. This paper presented a two-step processing scheme; a first stage is finding R-peak in the Electrocardiogram (ECG) by Shannon energy envelope estimator and a secondary stage is computing the interpolated peak location by parabola approximation. Experimental results show that the proposed algorithm performs better than with the previous method using low sampled ECG signals.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.2
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• pp.103-108
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• 1989

PERT formulae for the mean and variance of activity time are near exact only over a short interval of the concentration parameter which is defined as the sum of the two shape parameters of the beta distribution. Aiming a better estimation of the mean and variance of activity time, we propose a method of subjectively estimating this concentration parameter via estimating the probability of completing the activity within a specified time interval.

• Journal of Applied Reliability
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• v.2 no.2
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• pp.113-119
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• 2002

The estimation of mean lifetimes in presence of interval censoring with replacement procedure are 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. The maximum likelihood estimator is found in an implicit form. The Cramer-Rao lower bounds of the estimates are found in places of variances and by simulations the properties of the estimates are examined.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.269-277
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• 1994

Bootstrap approximation is compared with ordinary asymptotic method in the context of minimum chi-square estimation through application in a real problem. Fixed interval search method is shown to be superior over a random interval search method or Newton-Raphson method. All the procedures are implemented by S-Plus functions.

• Journal of Applied Reliability
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• v.1 no.2
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• pp.175-181
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• 2001

Recently, the quality of software has become a major issue. The statistical models used in making predictions about the quality of software are termed software reliability growth models (SRGM). However, the existing SRGMs have not been satisfactory in predicting software reliability behavior (Keiller and Miller(1991), Keiller and Littlewood(1984), Musa(1987)). In this paper, we present a fuzzy-based interval estimation of software errors (failures).

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.447-454
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• 2004

In this paper, we consider the bootstrap method to the interval estimation of the difference of quantiles of right censored data. We showed the validity of bootstrap method and compare with others with real data example. In simulation various resampling schemes for right censored data are also considered.

• Journal of the Korean Statistical Society
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• v.24 no.1
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• pp.161-181
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• 1995

The goal of this article is to study the performances of various empirical Bayes simultaneous interval estimates for all pairwise comparisons. The considered empirical Bayes interval estimaters are those based on unbiased estimate, a hierarchical Bayes estimate and a constrained hierarchical Bayes estimate. Simulation results for small sample cases are given and an illustrative example is also provided.

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.551-562
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• 1995

We consider the iterated bootstrap method in regression model with heterogeneous error variances. The iterated wild bootstrap confidence intervla of the mean response is considered. It is shown that the iterated wild bootstrap confidence interval has coverage error of order $n^{-1}$ wheresa percentile method interval has an error of order $n^{-1/2}$. The simulation results reveal that the iterated bootstrap method calibrates the coverage error of percentile method interval successfully even for the small sample size.

• 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.