• Journal of applied mathematics & informatics
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• 제7권2호
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• pp.467-482
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• 2000

Testing equality of two and k distributions has long been an interesting issue in statistical inference. To overcome the sparseness of data points in high-dimensional space and deal with the general cases, we suggest several projection pursuit type statistics. Some results on the limiting distributions of the statistics are obtained, some properties of Bootstrap approximation are investigated. Furthermore, for computational reasons an approximation for the statistics the based on Number theoretic method is applied. Several simulation experiments are performed.

• Journal of the Korean Statistical Society
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• 제20권2호
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• pp.99-107
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• 1991

Behrens-Fisher problem is viewed from a model selection approach. Normal distribution is regarded as an approximating model, A criterion, called TIC, is derived and is compared with selection criteria such as AIC and a bootstrap estimator. Stochastic approximation is used since no closed form expression is available for the bootstrap estimator.

• Communications for Statistical Applications and Methods
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• 제7권1호
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• pp.233-244
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• 2000

Confidence intervals for survival function give useful information about the lifetime distribution. In this paper we develop Edgeworkth expansions as approximation to the true and bootstrap distributions of normalized nonparametric maximum likelihood estimator of survival function in the Koziol-Green model and then use these results to show that the bootstrap approximations have second order accuracy.

• Journal of the Korean Statistical Society
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• 제26권3호
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• pp.383-395
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• 1997

This paper proves that the standard bootstrap approximation for the least absolute deviation (LAD) estimate of .beta. in AR(1) processes with infinite variance error terms is asymptotically valid in probability when the bootstrap resample size is much smaller than the original sample size. The theoretical validity results are supported by simulation studies.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 춘계 학술대회 논문집
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• pp.169-169
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• 2001

With the aid of fast computing power, resampling techniques are being introduced for simulation output analysis (SOA). Autocorrelation among the output from discrete-event simulation prohibit the direct application of resampling schemes (Threshold bootstrap, Binary bootstrap, Stationary bootstrap, etc) extend its usage to time-series data such as simulation output. We present a new method for inference from a regenerative process, regenerative bootstrap, that equals or exceeds the performance of classical regenerative method and approximation regeneration techniques. Regenerative bootstrap saves computation time and overcomes the problem of scarce regeneration cycles. Computational results are provided using M/M/1 model.

• Journal of the Korean Statistical Society
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• 제24권1호
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• pp.1-18
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• 1995

The generalized logit model of nominal type with random regressors is studied for bootstrapping. In particular, asymptotic normality and consistency of bootstrap model estimators are derived. It is shown that the bootstrap approximation to the distribution of the maximum likelihood estimators is valid for alsomt all sample sequences.

• Journal of the Korean Statistical Society
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• 제26권4호
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• pp.543-554
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• 1997

A family of some capability indices { $C_{p}$(.alpha.,.beta.); .alpha..geq.0, .beta..geq.0}, containing the indices $C_{p}$, $C_{{pk}}$, $C_{{pm}}$, and $C_{{pmk}}$, has been defined by Vannman(1993) for the case of two-sided specification interval. By varying the parameters of the family various capability indices with suitable properties are obtained. We derive tha asymptotic distribution of the family { $C_{p}$(.alpha.,.beta.); .alpha..geq.0,.beta..geq.0} under general proper conditions. It is also shown that the bootstrap approximation to the distribution of the estimator $C_{p}$(.alpha., .beta.) is vaild for almost all sample sequences. These asymptotic distributions would be used in constructing some bootstrap confidence intervals.tervals.

• 응용통계연구
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• 제22권1호
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• pp.153-161
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• 2009

We consider a logistic model with random effects as the superpopulation for estimating the small area pro-portions. The best linear unbiased predictor under linear mired model is popular in small area estimation. We use this type of estimator under logistic mixed motel for the small area proportions, on which the estimation of mean squared error is also discussed. Two kinds of estimation methods, the parametric bootstrap and the linear approximation will be compared through a Monte Carlo study in the respects of the normality assumption on the random effects distribution and also the magnitude of sample sizes on the approximation.

• Journal of the Korean Statistical Society
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• 제21권2호
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• pp.139-151
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• 1992

Simultaneous confidence intervals for the parameters in the logistic regression models with random regressors are considered. A method based on the bootstrap and its stochastic approximation will be developed. A key idea in using the bootstrap method to construct simultaneous confidence intervals is the concept of prepivoting which uses the transformation of a root by its estimated cumulative distribution function. Repeated use of prepivoting makes the overall coverage probability asymptotically correct and the coverage probabilities of the individual confidence statement asymptotically equal. This method is compared with ordinary asymptotic methods based on Scheffe's and Bonferroni's through Monte Carlo simulation.

• 응용통계연구
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• 제7권2호
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• pp.269-277
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• 1994

최소카이제곱추정에 의하여 구한 추정량의 표본분포를 붓스트랩으로 근사시켰을 때에도 정규근사와 최소한 동등함을 설명하고, 이 이론을 자궁경부암 조직에서 검출되는 란게르한스 세포의 출현률 추정에 이용하였다. 란게르한스 세포의 출현횟수를 포지티브 포아송 모형에 적합시켰으며, 추정된 출현률의 표준오차는 대표본 근사 및 붓스트랩을 이용하여 계산하였다. 두 방법 모두 비슷한 결과를 제공하였다.