• Communications for Statistical Applications and Methods
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• v.3 no.3
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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

• Journal of the Korean Statistical Society
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• v.23 no.1
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• pp.53-62
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• 1994

When a comparison is made with respect to the unknown best treatment, Hsu (1984, 1985) proposed the so called multiple comparisons procedures with the best in the analysis of variance model. Applying Hsu's results to the analysis of covariance model, simultaneous confidence intervals for multiple comparisons with the best in a balanced one-way layout with a random covariate are developed and are applied to a real data example.

• Journal of the Korean Statistical Society
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• v.31 no.2
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• pp.143-152
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• 2002

In an effort to make a right choice among ratio estimation strategies and PPS sampling strategies, we conduct an empirical investigation of the relative performances of three ratio estimation strategies and four PPS estimation strategies using a set of 12 natural populations. The quality of a strategy is measured in the traditional way, namely with the consideration of efficiency, achieved coverage rate of the nominal 99% confidence interval and approach to normality (asymmetry).

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.541-548
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• 1997

In regression model with nested error structure interval estimations on regression coefficients in different stages are proposed. Ordinary least square estimators and generalized least square estimators of the regression coefficients in this model are derived for between and within group model. The confidence intervals are dervied by using independent idstributional properties between regression coefficient estimators and quadratic froms obtained from the model.

• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.81-93
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• 2015

Validity of the stationary bootstrap of Politis and Romano (1994) is proved for U-statistics under strong mixing. Weak and strong consistencies are established for the stationary bootstrap of U-statistics. The theory is applied to a symmetry test which is a U-statistic regarding a kernel density estimator. The theory enables the bootstrap confidence intervals of the means of the U-statistics. A Monte-Carlo experiment for bootstrap confidence intervals confirms the asymptotic theory.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.293-303
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• 1999

When test outcomes of units are dichotomous and he infection rate is small group testing is more efficient that noe-to-one testing in estimating the true p and classifying units as infected or not. In this paper two-sided hypothesis testing and confidence intervals are derived based on the UMP(uniformly most powerful) unbiased test. The UMP unbiased approach is compared with Thompson's and Bhattacharyya et al.'s approaches by computing the length of confidence intervals and capture probabilities and shown to have a number of desirable properties. Unequal allocation one of advantages of the proposed approach is also mentioned.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.611-620
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• 1999

We shall propose several estimators and confidence intervals for the scale parameter in a uniform distribution with the presence of a generalized uniform outlier and obtain mean squared errors(MSE) for their proposed estimators. And we shall compare numerical MSE's for the proposed several estimators of the scale parameter. Also we shall compare numerically expected lengths of confidence intervals of the scale parameter in a uniform distribution with the presence of a generalized uniform outlier.

• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.837-845
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• 1998

We shall propose several estimators and confidence intervals for the scale parameter in a uniform distribution with the presence of a unidentified outlier and obtain biases and mean squared errors for their proposed estimators. And we shall numerically compare the performances for the proposed several estimators of the sclae parameter. Also, we shall compare lengths of confidence intervals of the scale parameter in a uniform distribution through Monte Carlo methods.

• Journal of the Korean Statistical Society
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• v.26 no.3
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• pp.309-317
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• 1997

A sequential procedure for estimating a linear function of two normal means which satisfies the two requirements, i.e. one is a condition of coverage probability, the other is a condition of $\beta$-protection, is proposed when the variances are unknown and not necessarily equal. We give asymptotic behaviors of the proposed stopping time.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.261-270
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• 2002

In this paper, we demonstrate the more accurate confidence intervals for median survival time under the simple proportional hazard model of Koziol and Green (1976) via the Edgeworth expansion for the distribution of the studentized ACL estimator derived in Jeong (2000). The numerical results show that the intervals, so-called test-based and reflect intervals (Slud et al., 1984), outperform normal approximating method in the small sample sizes and/or heavy censoring.