• Communications for Statistical Applications and Methods
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• 제6권2호
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• pp.383-395
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• 1999

This study is concerned with the evaluation of predictive ability of classification models with ordered multiple categories. If categories can be ordered or ranked the spread of misclassification should be considered to evaluate the performance of the classification models using loss rate since the apparent error rate can not measure the spread of misclassification. Since loss rate is known to underestimate the true loss rate the bootstrap method were used to estimate the true loss rate. thus this study suggests the method to evaluate the predictive power of the classification models using loss rate and the bootstrap estimate of the true loss rate.

• Journal of the Korean Data and Information Science Society
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• 제14권4호
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• pp.759-772
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• 2003

K-Means and Web mining modelling have been tried for finding major DNA marker of BM4311 microsatellite loci in Hanwoo Chromosome 6 linkage map. Furthermore, a major DNA mining by bootstrap simulations(BCa) has been applied.

• 응용통계연구
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• 제3권1호
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• pp.121-141
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• 1990

컴퓨터의 발전에 따른 통계방법 중에서 붓스트랩(bootstrap)에 대하여 연구하였다. 특히 추축통계량의 표본분포를 붓스트랩분포로 추정하는데 있어서 계산문제와 이론적인 정당성을 고려하였으며, 모분포의 성격을 나타내는 모수의 붓스트랩 신뢰영역을 몇 가지 사례들에 대해 살펴보았고 사례별로 붓스트랩 방법의 의미를 고찰하였다.

• Journal of the Korean Statistical Society
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• 제30권4호
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• pp.645-660
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• 2001

In this paper we propose a goodness-of-fit test statistic for testing the (null) parametric model versus the (alternative) nonparametric model. Most of existing nonparametric test statistics are based on the residuals which are obtained by regressing the data to a parametric model. Our test is based on the bootstrap estimator of the probability that the smoothing parameter estimator is infinite when fitting residuals to cubic smoothing spline. Power performance of this test is investigated and is compared with many other tests. Illustrative examples based on real data sets are given.

• Communications for Statistical Applications and Methods
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• 제3권1호
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• pp.257-265
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• 1996

We consider nonstationary autoregressive autoregressive process with infinite variance of error. In the case of infinite cariance, the limiting distribution of the estimated coefficient is different from that under the finite cariance assumption. In this paper we show that the bootstrap method can be used to approximate the distribution of ordinary least squares estimator of the coefficient in the first order random walk process with infinite variance through some empirical studies and we suggest a test procedure based on bootstrap method for the unit root test.

• Communications for Statistical Applications and Methods
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• 제16권6호
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• pp.1047-1054
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• 2009

Local smoothing jump detection procedure is a popular method for detecting jump locations and the performance of the jump detector heavily depends on the choice of the bandwidth. However, little work has been done on this issue. In this paper, we propose the bootstrap bandwidth selection method which can be used for any kernel-based or local polynomial-based jump detector. The proposed bandwidth selection method is fully data-adaptive and its performance is evaluated through a simulation study and a real data example.

• 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.

• Communications for Statistical Applications and Methods
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• 제4권3호
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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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• 제15권3호
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• pp.625-632
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• 2004

We consider the empirical Bayes confidence intervals that attain a specified level of EB coverage for the scale parameter in the Burr distribution under type II censoring data. Also, we compare the coverage probabilities and the expected confidence interval lengths for these confidence intervals through simulation study.

• Journal of the Korean Data and Information Science Society
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• 제15권1호
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• pp.107-117
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• 2004

Change point testing problem is considered. Kernel density estimators are used for constructing proposed change point test statistics. The proposed method can be used to the hypothesis testing of not only parameter change but also distributional change. Bootstrap method is applied to get the sampling distribution of proposed test statistic. Small sample Monte Carlo Simulation were also conducted in order to show the performance of proposed method.